PUBLIKATIONSSERVER

Thorsten Jungeblut

https://orcid.org/0000-0001-7425-8766

74 Publikationen

Alle markieren

[74]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6365
Köse MI, Ahmed QA, Jungeblut T. Bridging the Gap Between AI Quantization and Edge Deployment: INT4 and INT8 on the Edge. In: NeurIPS 2025 , ed. The 5th Muslims in Machine Learning (MusIML) Workshop Co-Located with NeurIPS 2025. San Diego, CA, USA.; 2025.
HSBI-PUB | Download (ext.)
 
[73]
2025 | Konferenzbeitrag | FH-PUB-ID: 6355
Attaullah H, Peters C, Peters A, Jungeblut T. AI Meets Elderly Care: Mining Smart Home Data for Dementia and Depression Detection. Schriftenreihe des Institute for Data Science Solutions, ed. 2025;2:38-39. doi:10.60802/SIDAS.2025.2
HSBI-PUB | Dateien verfügbar | DOI
 
[72]
2025 | Artikel | FH-PUB-ID: 6139
Attaullah H, Sanaullah S, Peters A, Ahmed QA, Baudisch J, Jungeblut T. DNA: detecting early signs of neurodegenerative diseases through activity and sleep analysis. Frontiers in Neuroscience. 2025;19. doi:10.3389/fnins.2025.1617758
HSBI-PUB | DOI
 
[71]
2025 | Konferenzbeitrag | FH-PUB-ID: 6073 | OA
Jalil F, Awais M, Ahmed QA, Mohammadi HG, Jungeblut T, Platzner M. Deep&Wide: Achieving Area Efficiency in Scalable Approximate Accelerators. In: Institute of Electrical and Electronics Engineers (IEEE), ed. 2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W). IEEE; 2025:115-118. doi:10.1109/DSN-W65791.2025.00048
HSBI-PUB | DOI | Download (ext.)
 
[70]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6080
Jalil F, Leuering J, Ahmed QA, Schenck W, Jungeblut T. NNXC: Neural Network Meets Approximate Computing. In: Bielefeld: Institute for Data Science Solutions; 2025.
HSBI-PUB
 
[69]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6082
Wermuth S, Ahmed QA, Jungeblut T. From Fisheye to Fusion: Towards Efficient AI-based Indoor Perception for Public Transportation. In: Workshop on AI and Its Applications. Bielefeld: Institute for Data Science Solutions; 2025.
HSBI-PUB
 
[68]
2025 | Konferenzbeitrag | FH-PUB-ID: 6140
Ahmed QA, Mughal DM, Munir D, et al. MALRIS: Malicious Hardware in RIS-Assisted Wireless Communications. In: arXiv; 2025. doi:10.48550/ARXIV.2508.06340
HSBI-PUB | DOI
 
[67]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6083
Köse MI, Ahmed QA, Jungeblut T. Edge4OD: An Automated Framework for Efficient Execution of Object Detection Algorithms on Edge Devices. In: Bielefeld: Institute for Data Science Solutions; 2025. doi:10.60802/sidas.2025.2
HSBI-PUB | DOI
 
[66]
2025 | Konferenzbeitrag | FH-PUB-ID: 6204 | OA
Attaullah H, Halbrügge M, Naumann R, Jungeblut T. Digitaler Bahnhof Minden: Künstliche Intelligenz für den Bahnhof der Zukunft. In: ; 2025:4-5. doi:10.60802/sidas.2025.2
HSBI-PUB | DOI | Download (ext.)
 
[65]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6081
Jalil F, Leuering J, Ahmed QA, Schenck W, Jungeblut T. AutoDSE: Towards HW/AI Co-design of Ultra-low Latency Hardware Accelerators for Industrial Applications. In: Workshop on AI and Its Applications. Bielefeld: Institute for Data Science Solutions; 2025. doi:10.60802/sidas.2025.2
HSBI-PUB | DOI
 
[64]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6077
Leuering J, Jalil F, Ahmed QA, Schenck W, Jungeblut T. Cognitive Edge Computing for Multi-Sensor Applications with Sparse Data and High Latency Requirements. In: Bielefeld: Institute for Data Science Solutions.
HSBI-PUB
 
[63]
2025 | Konferenzbeitrag | FH-PUB-ID: 6302 | OA
Wermuth S, Jungeblut T. Bridging the Dataset Gap: Domain Adaptation for Fisheye Passenger Detection. In: KI2025@HSBI Zukunft Im Fokus. Schriftenreihe des Institute for Data Science Solutions. ; 2025:28-29. doi:10.60802/SIDAS.2025.2
HSBI-PUB | DOI | Download (ext.)
 
[62]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6175
Halbrügge M, Jungeblut T. Beyond Heatmaps: Evaluating LIME Visualizations for Human Understandability. In: Gesellschaft für Kognitionswissenschaft, ed. KogWis 2025. 16th Biannual Conference of the German Cognitive Science Society. ; 2025.
HSBI-PUB
 
[61]
2025 | Artikel | FH-PUB-ID: 6240 | OA
Jagemann I, Baudisch J, Jungeblut T, Maier GW, Hirschfeld G. The More You Know, the Less You Want to Rely on It – Consumer preferences for AI-based health monitoring in smart home systems. PsychArchives. 2025. doi:10.23668/PSYCHARCHIVES.21275
HSBI-PUB | DOI | Download (ext.)
 
[60]
2025 | Konferenzbeitrag | FH-PUB-ID: 6206 | OA
Kwossek J, Eris B, Bollien M, et al. AQ-Shuttle: Autonomous Robots for Last Mile Delivery. In: Workshop on Autonomous Delivery and Service Robots on Pedestrian and Cycle Paths. ; 2025.
HSBI-PUB | Download (ext.)
 
[59]
2025 | Konferenzbeitrag | FH-PUB-ID: 6205
Kwossek J, Eris B, Bollien M, et al. Autonomous District Shuttles for Last-Mile Delivery: Acceptance, Public Requirements, and Their Role in Urban Development. In: HUMANIST Conference 2025. ; 2025.
HSBI-PUB
 
[58]
2025 | Konferenzbeitrag | FH-PUB-ID: 6202 | OA
Halbrügge M, Jungeblut T. Statistical Learning of Daily Routines in the Smart Home for Privacy-Preserving Assisted Living. In: KI@HSBI 2025 - Zukunft Im Fokus. ; 2025:13-14. doi:10.60802/sidas.2025.2
HSBI-PUB | DOI | Download (ext.)
 
[57]
2025 | Konferenzbeitrag | FH-PUB-ID: 6203 | OA
Kaan A, Eris B, Halbrügge M, et al. AQ-Shuttle: Eine Studie über autonome Quartiers-Shuttle mit Mobilstation in Bielefeld. In: ; 2025:2-3. doi:10.60802/sidas.2025.2
HSBI-PUB | DOI | Download (ext.)
 
[56]
2025 | Konferenzbeitrag | FH-PUB-ID: 5976
Sanaullah S, Honda H, Roy K, Schneider A, Waßmuth J, Jungeblut T. Automating Neural Model Selection in Spiking Neural Networks Using AutoML Techniques*. In: 2025 22nd International Learning and Technology Conference (L&T). IEEE; 2025:274-279. doi:10.1109/LT64002.2025.10941536
HSBI-PUB | DOI
 
[55]
2025 | Artikel | FH-PUB-ID: 5366
Sanaullah S, Schneider A, Waßmuth J, Rückert U, Jungeblut T. RAVSim v2.0: Enhanced visualization and comparative analysis for neural network models. SoftwareX. 2025;29. doi:10.1016/j.softx.2024.102006
HSBI-PUB | DOI
 
[54]
2024 | Konferenzbeitrag | FH-PUB-ID: 5061 | OA
Ahmed QA, Sadeghi-Kohan S, Awais M, et al. RelaX: Reliability Assessment in Approximate Circuits. In: ; 2024.
HSBI-PUB | Dateien verfügbar | Download (ext.)
 
[53]
2024 | Konferenzbeitrag | FH-PUB-ID: 4782
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. A Spike Vision Approach for Multi-object Detection and Generating Dataset Using Multi-core Architecture on Edge Device. In: Iliadis L, Maglogiannis I, Papaleonidas A, Pimenidis E, Jayne C, eds. Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings. Communications in Computer and Information Science. Cham: Springer Nature Switzerland; 2024:317-328. doi:10.1007/978-3-031-62495-7_24
HSBI-PUB | DOI
 
[52]
2024 | Konferenzbeitrag | FH-PUB-ID: 5367 | OA
Koravuna S, Sanaullah S, Jungeblut T, Rückert U. Spiking Neural Network Models Analysis on Field Programmable Gate Arrays. In: Pudaruth S, Ogudo K, eds. International Conference on Intelligent and Innovative Computing Applications. Vol 2024. Society of Information Technologists and Engineers Ltd; 2024:259-270. doi:10.59200/ICONIC.2024.027
HSBI-PUB | DOI | Download (ext.)
 
[51]
2024 | Diskussionspapier | FH-PUB-ID: 5498
Hammer B, Alaçam Ö, Arlinghaus CS, et al. Sustainable Life-Cycle of Intelligent Socio-Technical Systems. Bielefeld University; 2024. doi:10.4119/UNIBI/2992602
HSBI-PUB | DOI
 
[50]
2024 | Konferenzbeitrag | FH-PUB-ID: 5336
Attaullah H, Kiani A, Jungeblut T. Improving Transfer Learning and Domain Adaptation in Smart Homes: The Role of Dynamic Domain Adaptation Layer. In: IEEE, ed. 2024 International Conference on Frontiers of Information Technology (FIT). IEEE; 2024:1-6. doi:10.1109/FIT63703.2024.10838396
HSBI-PUB | DOI
 
[49]
2024 | Konferenzbeitrag | FH-PUB-ID: 5315
Attaullah H, Sanaullah S, Jungeblut T. FL-DL: Fuzzy Logic with Deep Learning, Hybrid Anomaly Detection and Activity Prediction in Smart Homes Data-Sets. In: 2024 IEEE 24th International Symposium on Computational Intelligence and Informatics (CINTI). Budapest, Hungary: IEEE; 2024:43-48. doi:10.1109/CINTI63048.2024.10830825
HSBI-PUB | DOI
 
[48]
2024 | Konferenzbeitrag | FH-PUB-ID: 5098
Sanaullah S, Attaullah H, Jungeblut T. Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications. In: Omitaomu OA, Mostafavi A, Randhawa S, Niu H, eds. Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI. New York, NY, USA: ACM; 2024:50-53. doi:10.1145/3681780.3697244
HSBI-PUB | DOI
 
[47]
2024 | Konferenzbeitrag | FH-PUB-ID: 5097
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Advancements in Neural Network Generations. In: Kuhl U, DataNinja.nrw, eds. Proceedings of the SAIOnARA Conference. DataNinja sAIOnARA Conference; 2024. doi:10.11576/DATANINJA-1167
HSBI-PUB | DOI
 
[46]
2024 | Konferenzbeitrag | FH-PUB-ID: 5096
Sanaullah S, Attaullah H, Jungeblut T. Trade-offs Between Privacy and Performance in Encrypted Dataset using Machine Learning Models. In: Kuhl U, DataNinja.nrw, eds. Proceedings of the SAIOnARA Conference. DataNinja sAIOnARA Conference; 2024. doi:10.11576/DATANINJA-1166
HSBI-PUB | DOI
 
[45]
2024 | Artikel | FH-PUB-ID: 4997 | OA
Attaullah H, Sanaullah S, Jungeblut T. Analyzing Machine Learning Models for Activity Recognition Using Homomorphically Encrypted Real-World Smart Home Datasets: A Case Study. Applied Sciences. 2024;14(19). doi:10.3390/app14199047
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[44]
2024 | Kurzbeitrag Konferenz | FH-PUB-ID: 4883
Sanaullah S, Roy K, Ruckert U, Jungeblut T. Selection of Optimal Neural Model using Spiking Neural Network for Edge Computing  . In: IEEE, ed. 2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS). IEEE; 2024:1452-1453. doi:10.1109/ICDCS60910.2024.00147
HSBI-PUB | DOI | Inspire
 
[43]
2024 | Konferenzbeitrag | FH-PUB-ID: 4811
Sanaullah S, Attaullah H, Jungeblut T. The Next-Gen Interactive Runtime Simulator for Neural Network Programming. In: Söderberg E, Church L, eds. Companion Proceedings of the 8th International Conference on the Art, Science, and Engineering of Programming. New York, NY, USA: ACM; 2024:8-10. doi:10.1145/3660829.3660833
HSBI-PUB | DOI
 
[42]
2024 | Konferenzbeitrag | FH-PUB-ID: 4783 | OA
Sanaullah S, Roy K, Rückert U, Jungeblut T. A Hybrid Spiking-Convolutional Neural Network Approach for Advancing Machine Learning Models. In: Lutchyn T, Ramírez Rivera A, Ricaud B, eds. Proceedings of the 5th Northern Lights Deep Learning Conference. Vol 233. UiT The Arctic University, Tromsø, Norway: Proceedings of Machine Learning Research (PMLR); 2024. doi:10.48550/arXiv.2407.08861
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.) | WoS | arXiv
 
[41]
2024 | Kurzbeitrag Konferenz | FH-PUB-ID: 4639 | OA
Herzig TC, Marschner C, Held S, et al. KI-gestütztes Monitoring zur Unterstützung in der häuslichen Pflege (KIMUP) . In: Institute for Data Science Solutions, ed. Kongress KI@HSBI2023 Solutions im Fokus - Posterbeiträge . Vol 1. Kongress KI@HSBI2023 Solutions im Fokus - Posterbeiträge . Bielefeld: Hochschule Bielefeld; 2024:9-10. doi:10.60802/sidas.2024.1
HSBI-PUB | DOI | Download (ext.)
 
[40]
2023 | Buchbeitrag | FH-PUB-ID: 3222
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Streamlined Training of GCN for Node Classification with Automatic Loss Function and Optimizer Selection. In: Iliadis L, Maglogiannis I, Alonso S, Jayne C, Pimenidis E, eds. Engineering Applications of Neural Networks. 24th International Conference, EAAAI/EANN 2023, León, Spain, June 14–17, 2023, Proceedings. Communications in Computer and Information Science. Cham: Springer Nature Switzerland; 2023:191-202. doi:10.1007/978-3-031-34204-2_17
HSBI-PUB | DOI
 
[39]
2023 | Artikel | FH-PUB-ID: 3482 | OA
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Evaluation of Spiking Neural Nets-Based Image Classification Using the Runtime Simulator RAVSim. International Journal of Neural Systems. 2023. doi:10.1142/S0129065723500442
HSBI-PUB | DOI | Download (ext.)
 
[38]
2023 | Artikel | FH-PUB-ID: 3572 | OA
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications. Frontiers in Computational Neuroscience. 2023;17. doi:10.3389/fncom.2023.1215824
HSBI-PUB | DOI | Download (ext.)
 
[37]
2023 | Artikel | FH-PUB-ID: 3666
Koravuna S, Rückert U, Jungeblut T. Evaluating Spiking Neural Network Models: A Comparative Performance Analysis. Preprint. 2023. doi:10.13140/RG.2.2.21295.71847
HSBI-PUB | DOI
 
[36]
2023 | Artikel | FH-PUB-ID: 3665 | OA
Sanaullah S, Koravuna S, Ruckert U, Jungeblut T. Design-Space Exploration of SNN Models using Application-Specific Multi-Core Architectures. Preprint. 2023. doi:10.13140/RG.2.2.26328.88324
HSBI-PUB | DOI | Download (ext.)
 
[35]
2023 | Konferenzbeitrag | FH-PUB-ID: 3644 | OA
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Transforming Event-Based into Spike-Rate Datasets for Enhancing Neuronal Behavior Simulation to Bridging the Gap for SNNs. In: Paris France ; 2023. doi:10.13140/RG.2.2.14469.32485
HSBI-PUB | DOI | Download (ext.)
 
[34]
2023 | Konferenzbeitrag | FH-PUB-ID: 4207 | OA
Sanaullah S, Jungeblut T. Analysis of MR Images for Early and Accurate Detection of Brain Tumor using Resource Efficient Simulator Brain Analysis. In: New York USA; 2023. doi:10.5281/zenodo.10457930
HSBI-PUB | DOI | Download (ext.)
 
[33]
2023 | Kurzbeitrag Konferenz | FH-PUB-ID: 4206 | OA
Sanaullah S, Amanullah A, Roy K, Lee J-A, Chul-Jun S, Jungeblut T. A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting. In: ; 2023. doi:10.5281/zenodo.10458019
HSBI-PUB | DOI | Download (ext.)
 
[32]
2023 | Konferenzbeitrag | FH-PUB-ID: 4205 | OA
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. A Novel Spike Vision Approach for Robust Multi-Object Detection using SNNs. In: ; 2023. doi:10.5281/zenodo.10262228
HSBI-PUB | DOI | Download (ext.)
 
[31]
2023 | Konferenzbeitrag | FH-PUB-ID: 4208
Koravuna S, Sanaullah S, Jungeblut T, Rückert U. Digit Recognition Using Spiking Neural Networks on FPGA. In: Rojas I, Joya G, Catala A, eds. Advances in Computational Intelligence. 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, Ponta Delgada, Portugal, June 19–21, 2023, Proceedings, Part I. Lecture Notes in Computer Science. Cham: Springer Nature Switzerland; 2023:406-417. doi:10.1007/978-3-031-43085-5_32
HSBI-PUB | DOI
 
[30]
2022 | Konferenzbeitrag | FH-PUB-ID: 2757
Sanaullah S, Koravuna S, Jungeblut T, Rückert U. NireHApS: Neuro-Inspired and Resource-Efficient Hardware-Architectures for Plastic SNNs. In: ; 2022. doi:10.13140/RG.2.2.16202.85444
HSBI-PUB | DOI
 
[29]
2022 | Artikel | FH-PUB-ID: 4482 | OA
Baudisch J, Richter B, Jungeblut T. A Framework for Learning Event Sequences and Explaining Detected Anomalies in a Smart Home Environment. KI - Künstliche Intelligenz. 2022;36(3-4):259-266. doi:10.1007/s13218-022-00775-5
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[28]
2022 | Kurzbeitrag Konferenz | FH-PUB-ID: 2753
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Real-Time Resource Efficient Simulator for SNNs-based Model Experimentation. 2022. doi:10.13140/RG.2.2.24761.85607
HSBI-PUB | DOI
 
[27]
2022 | Konferenzbeitrag | FH-PUB-ID: 3480 | OA
Sanaullah S, Koravuna S, Ruckert U, Jungeblut T. Real-Time SNNs Model Analyzing and Visualizing Experimentation. In: Unpublished; 2022. doi:10.13140/RG.2.2.14584.83201/1
HSBI-PUB | DOI | Download (ext.)
 
[26]
2022 | Konferenzbeitrag | FH-PUB-ID: 2276
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. SNNs Model Analyzing and Visualizing Experimentation Using RAVSim. In: Iliadis L, Jayne C, Tefas A, Pimenidis E, eds. Engineering Applications of Neural Networks. 23rd International Conference, EAAAI/EANN 2022, Chersonissos, Crete, Greece, June 17–20, 2022, Proceedings. Communications in Computer and Information Science. Cham: Springer International Publishing; 2022:40-51. doi:10.1007/978-3-031-08223-8_4
HSBI-PUB | DOI
 
[25]
2019 | Konferenzbeitrag | FH-PUB-ID: 4483
Adams M, Ben-Salem S, Islam Z, et al. Towards an SSVEP-BCI Controlled Smart Home. In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE; 2019:2737-2742. doi:10.1109/SMC.2019.8914668
HSBI-PUB | DOI
 
[24]
2018 | Artikel | FH-PUB-ID: 4486
Ax J, Sievers G, Daberkow J, et al. CoreVA-MPSoC: A Many-Core Architecture with Tightly Coupled Shared and Local Data Memories. IEEE Transactions on Parallel and Distributed Systems. 2018;29(5):1030-1043. doi:10.1109/TPDS.2017.2785799
HSBI-PUB | DOI
 
[23]
2018 | Konferenzbeitrag | FH-PUB-ID: 4485
Gayen N, Ax J, Flasskamp M, et al. Scalable Mapping of Streaming Applications onto MPSoCs Using Optimistic Mixed Integer Linear Programming. In: 2018 26th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). IEEE; 2018:348-352. doi:10.1109/PDP2018.2018.00062
HSBI-PUB | DOI
 
[22]
2018 | Konferenzbeitrag | FH-PUB-ID: 4487
Cristal A, Unsal OS, Martorell X, et al. LEGaTO. In: Proceedings of the 15th ACM International Conference on Computing Frontiers. New York, NY, USA: ACM; 2018:276-278. doi:10.1145/3203217.3205339
HSBI-PUB | DOI
 
[21]
2018 | Konferenzbeitrag | FH-PUB-ID: 4484
Cristal A, Unsal OS, Martorell X, et al. LEGaTO. In: Proceedings of the 18th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation. New York, USA: ACM; 2018:210-217. doi:10.1145/3229631.3239370
HSBI-PUB | DOI
 
[20]
2017 | Buchbeitrag | FH-PUB-ID: 4490
Sievers G, Hübener B, Ax J, et al. The CoreVA-MPSoC: A Multiprocessor Platform for Software-Defined Radio. In: Hussain W, Nurmi J, Isoaho J, Garzia F, eds. Computing Platforms for Software-Defined Radio. Cham: Springer International Publishing; 2017:29-59. doi:10.1007/978-3-319-49679-5_3
HSBI-PUB | DOI
 
[19]
2017 | Konferenzbeitrag | FH-PUB-ID: 4489
Hesse M, Krause AF, Vogel L, et al. A connected chair as part of a smart home environment. In: 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks (BSN). IEEE; 2017:47-50. doi:10.1109/BSN.2017.7936004
HSBI-PUB | DOI
 
[18]
2017 | Konferenzbeitrag | FH-PUB-ID: 4488
Vohrmann M, Geisler P, Jungeblut T, Ruckert U. Design-space exploration of ultra-low power CMOS logic gates in a 28 nm FD-SOI technology. In: 2017 European Conference on Circuit Theory and Design (ECCTD). IEEE; 2017:1-4. doi:10.1109/ECCTD.2017.8093232
HSBI-PUB | DOI
 
[17]
2016 | Konferenzbeitrag | FH-PUB-ID: 4491
Flasskamp M, Sievers G, Ax J, et al. Performance estimation of streaming applications for hierarchical MPSoCs. In: Proceedings of the 2016 Workshop on Rapid Simulation and Performance Evaluation: Methods and Tools. New York, NY, USA: ACM; 2016:1-6. doi:10.1145/2852339.2852342
HSBI-PUB | DOI
 
[16]
2015 | Konferenzbeitrag | FH-PUB-ID: 4496
Ax J, Sievers G, Flasskamp M, Kelly W, Jungeblut T, Porrmann M. System-Level Analysis of Network Interfaces for Hierarchical MPSoCs. In: Proceedings of the 8th International Workshop on Network on Chip Architectures. New York, NY, USA: ACM; 2015:3-8. doi:10.1145/2835512.2835513
HSBI-PUB | DOI
 
[15]
2015 | Konferenzbeitrag | FH-PUB-ID: 4494
Sievers G, Ax J, Kucza N, et al. Evaluation of interconnect fabrics for an embedded MPSoC in 28 nm FD-SOI. In: 2015 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE; 2015:1925-1928. doi:10.1109/ISCAS.2015.7169049
HSBI-PUB | DOI
 
[14]
2015 | Konferenzbeitrag | FH-PUB-ID: 4493
Sievers G, Daberkow J, Ax J, et al. Comparison of Shared and Private L1 Data Memories for an Embedded MPSoC in 28nm FD-SOI. In: 2015 IEEE 9th International Symposium on Embedded Multicore/Many-Core Systems-on-Chip. IEEE; 2015:175-181. doi:10.1109/MCSoC.2015.25
HSBI-PUB | DOI
 
[13]
2015 | Konferenzbeitrag | FH-PUB-ID: 4492
Vohrmann M, Chatterjee S, Lutkemeier S, Jungeblut T, Porrmann M, Rückert U. A 65 nm standard cell library for ultra low-power applications. In: 2015 European Conference on Circuit Theory and Design (ECCTD). IEEE; 2015:1-4. doi:10.1109/ECCTD.2015.7300041
HSBI-PUB | DOI
 
[12]
2014 | Konferenzbeitrag | FH-PUB-ID: 4498
Hübener B, Sievers G, Jungeblut T, Porrmann M, Rückert U. CoreVA: A Configurable Resource-Efficient VLIW Processor Architecture. In: 2014 12th IEEE International Conference on Embedded and Ubiquitous Computing. IEEE; 2014:9-16. doi:10.1109/EUC.2014.11
HSBI-PUB | DOI
 
[11]
2014 | Konferenzbeitrag | FH-PUB-ID: 4497
Kelly W, Flasskamp M, Sievers G, et al. A communication model and partitioning algorithm for streaming applications for an embedded MPSoC. In: 2014 International Symposium on System-on-Chip (SoC). IEEE; 2014:1-6. doi:10.1109/ISSOC.2014.6972436
HSBI-PUB | DOI
 
[10]
2014 | Konferenzbeitrag | FH-PUB-ID: 4495
Keuck L, Hemmelgarn F, Fröhleke N, et al. Neuro control of a PFC rectifier for harmonic reduction at partial loads. In: 2014 International Conference on Advances in Green Energy (ICAGE). IEEE; 2014:94-99. doi:10.1109/ICAGE.2014.7050149
HSBI-PUB | DOI
 
[9]
2013 | Konferenzbeitrag | FH-PUB-ID: 4502
Christ P, Sievers G, Einhaus J, Jungeblut T, Porrmann M, Rückert U. Pareto-optimal signal processing on low-power microprocessors. In: 2013 IEEE SENSORS. IEEE; 2013:1-4. doi:10.1109/ICSENS.2013.6688593
HSBI-PUB | DOI
 
[8]
2013 | Konferenzbeitrag | FH-PUB-ID: 4501
Sievers G, Christ P, Einhaus J, Jungeblut T, Porrmann M, Rückert U. Design-space exploration of the configurable 32 bit VLIW processor CoreVA for signal processing applications. In: 2013 NORCHIP. IEEE; 2013:1-4. doi:10.1109/NORCHIP.2013.6702002
HSBI-PUB | DOI
 
[7]
2013 | Artikel | FH-PUB-ID: 4500
Jungeblut T, Hübener B, Porrmann M, Rückert U. A systematic approach for optimized bypass configurations for application-specific embedded processors. ACM Transactions on Embedded Computing Systems. 2013;13(2):1-25. doi:10.1145/2514641.2514645
HSBI-PUB | DOI
 
[6]
2013 | Artikel | FH-PUB-ID: 4499
Lütkemeier S, Jungeblut T, Berge HKO, Aunet S, Porrmann M, Rückert U. A 65 nm 32 b Subthreshold Processor With 9T Multi-Vt SRAM and Adaptive Supply Voltage Control. IEEE Journal of Solid-State Circuits. 2013;48(1):8-19. doi:10.1109/JSSC.2012.2220671
HSBI-PUB | DOI
 
[5]
2012 | Konferenzbeitrag | FH-PUB-ID: 4504
Jungeblut T, Ax J, Porrmann M, Rückert U. A TCMS-based architecture for GALS NoCs. In: 2012 IEEE International Symposium on Circuits and Systems. IEEE; 2012:2721-2724. doi:10.1109/ISCAS.2012.6271870
HSBI-PUB | DOI
 
[4]
2012 | Konferenzbeitrag | FH-PUB-ID: 4503
Luetkemeier S, Jungeblut T, Porrmann M, Rückert U. A 200mV 32b subthreshold processor with adaptive supply voltage control. In: 2012 IEEE International Solid-State Circuits Conference. IEEE; 2012:484-486. doi:10.1109/ISSCC.2012.6177101
HSBI-PUB | DOI
 
[3]
2010 | Artikel | FH-PUB-ID: 4506
Jungeblut T, Puttmann C, Dreesen R, et al. Resource efficiency of hardware extensions of a 4-issue VLIW processor for elliptic curve cryptography. Advances in Radio Science. 2010;8:295-305. doi:10.5194/ars-8-295-2010
HSBI-PUB | DOI
 
[2]
2010 | Konferenzbeitrag | FH-PUB-ID: 4505
Jungeblut T, Sievers G, Porrmann M, Rückert U. Design Space Exploration for Memory Subsystems of VLIW Architectures. In: 2010 IEEE Fifth International Conference on Networking, Architecture, and Storage. IEEE; 2010:377-385. doi:10.1109/NAS.2010.14
HSBI-PUB | DOI
 
[1]
2008 | Artikel | FH-PUB-ID: 4507
Jungeblut T, Grünewald M, Porrmann M, Rückert U. Realtime multiprocessor for mobile ad hoc networks. Advances in Radio Science. 2008;6:239-243. doi:10.5194/ars-6-239-2008
HSBI-PUB | DOI
 
Markierte Publikation(en)

Suche

Publikationen filtern

Darstellung / Sortierung

Zitationsstil: AMA

Export / Einbettung

74 Publikationen

Alle markieren

[74]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6365
Köse MI, Ahmed QA, Jungeblut T. Bridging the Gap Between AI Quantization and Edge Deployment: INT4 and INT8 on the Edge. In: NeurIPS 2025 , ed. The 5th Muslims in Machine Learning (MusIML) Workshop Co-Located with NeurIPS 2025. San Diego, CA, USA.; 2025.
HSBI-PUB | Download (ext.)
 
[73]
2025 | Konferenzbeitrag | FH-PUB-ID: 6355
Attaullah H, Peters C, Peters A, Jungeblut T. AI Meets Elderly Care: Mining Smart Home Data for Dementia and Depression Detection. Schriftenreihe des Institute for Data Science Solutions, ed. 2025;2:38-39. doi:10.60802/SIDAS.2025.2
HSBI-PUB | Dateien verfügbar | DOI
 
[72]
2025 | Artikel | FH-PUB-ID: 6139
Attaullah H, Sanaullah S, Peters A, Ahmed QA, Baudisch J, Jungeblut T. DNA: detecting early signs of neurodegenerative diseases through activity and sleep analysis. Frontiers in Neuroscience. 2025;19. doi:10.3389/fnins.2025.1617758
HSBI-PUB | DOI
 
[71]
2025 | Konferenzbeitrag | FH-PUB-ID: 6073 | OA
Jalil F, Awais M, Ahmed QA, Mohammadi HG, Jungeblut T, Platzner M. Deep&Wide: Achieving Area Efficiency in Scalable Approximate Accelerators. In: Institute of Electrical and Electronics Engineers (IEEE), ed. 2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W). IEEE; 2025:115-118. doi:10.1109/DSN-W65791.2025.00048
HSBI-PUB | DOI | Download (ext.)
 
[70]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6080
Jalil F, Leuering J, Ahmed QA, Schenck W, Jungeblut T. NNXC: Neural Network Meets Approximate Computing. In: Bielefeld: Institute for Data Science Solutions; 2025.
HSBI-PUB
 
[69]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6082
Wermuth S, Ahmed QA, Jungeblut T. From Fisheye to Fusion: Towards Efficient AI-based Indoor Perception for Public Transportation. In: Workshop on AI and Its Applications. Bielefeld: Institute for Data Science Solutions; 2025.
HSBI-PUB
 
[68]
2025 | Konferenzbeitrag | FH-PUB-ID: 6140
Ahmed QA, Mughal DM, Munir D, et al. MALRIS: Malicious Hardware in RIS-Assisted Wireless Communications. In: arXiv; 2025. doi:10.48550/ARXIV.2508.06340
HSBI-PUB | DOI
 
[67]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6083
Köse MI, Ahmed QA, Jungeblut T. Edge4OD: An Automated Framework for Efficient Execution of Object Detection Algorithms on Edge Devices. In: Bielefeld: Institute for Data Science Solutions; 2025. doi:10.60802/sidas.2025.2
HSBI-PUB | DOI
 
[66]
2025 | Konferenzbeitrag | FH-PUB-ID: 6204 | OA
Attaullah H, Halbrügge M, Naumann R, Jungeblut T. Digitaler Bahnhof Minden: Künstliche Intelligenz für den Bahnhof der Zukunft. In: ; 2025:4-5. doi:10.60802/sidas.2025.2
HSBI-PUB | DOI | Download (ext.)
 
[65]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6081
Jalil F, Leuering J, Ahmed QA, Schenck W, Jungeblut T. AutoDSE: Towards HW/AI Co-design of Ultra-low Latency Hardware Accelerators for Industrial Applications. In: Workshop on AI and Its Applications. Bielefeld: Institute for Data Science Solutions; 2025. doi:10.60802/sidas.2025.2
HSBI-PUB | DOI
 
[64]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6077
Leuering J, Jalil F, Ahmed QA, Schenck W, Jungeblut T. Cognitive Edge Computing for Multi-Sensor Applications with Sparse Data and High Latency Requirements. In: Bielefeld: Institute for Data Science Solutions.
HSBI-PUB
 
[63]
2025 | Konferenzbeitrag | FH-PUB-ID: 6302 | OA
Wermuth S, Jungeblut T. Bridging the Dataset Gap: Domain Adaptation for Fisheye Passenger Detection. In: KI2025@HSBI Zukunft Im Fokus. Schriftenreihe des Institute for Data Science Solutions. ; 2025:28-29. doi:10.60802/SIDAS.2025.2
HSBI-PUB | DOI | Download (ext.)
 
[62]
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6175
Halbrügge M, Jungeblut T. Beyond Heatmaps: Evaluating LIME Visualizations for Human Understandability. In: Gesellschaft für Kognitionswissenschaft, ed. KogWis 2025. 16th Biannual Conference of the German Cognitive Science Society. ; 2025.
HSBI-PUB
 
[61]
2025 | Artikel | FH-PUB-ID: 6240 | OA
Jagemann I, Baudisch J, Jungeblut T, Maier GW, Hirschfeld G. The More You Know, the Less You Want to Rely on It – Consumer preferences for AI-based health monitoring in smart home systems. PsychArchives. 2025. doi:10.23668/PSYCHARCHIVES.21275
HSBI-PUB | DOI | Download (ext.)
 
[60]
2025 | Konferenzbeitrag | FH-PUB-ID: 6206 | OA
Kwossek J, Eris B, Bollien M, et al. AQ-Shuttle: Autonomous Robots for Last Mile Delivery. In: Workshop on Autonomous Delivery and Service Robots on Pedestrian and Cycle Paths. ; 2025.
HSBI-PUB | Download (ext.)
 
[59]
2025 | Konferenzbeitrag | FH-PUB-ID: 6205
Kwossek J, Eris B, Bollien M, et al. Autonomous District Shuttles for Last-Mile Delivery: Acceptance, Public Requirements, and Their Role in Urban Development. In: HUMANIST Conference 2025. ; 2025.
HSBI-PUB
 
[58]
2025 | Konferenzbeitrag | FH-PUB-ID: 6202 | OA
Halbrügge M, Jungeblut T. Statistical Learning of Daily Routines in the Smart Home for Privacy-Preserving Assisted Living. In: KI@HSBI 2025 - Zukunft Im Fokus. ; 2025:13-14. doi:10.60802/sidas.2025.2
HSBI-PUB | DOI | Download (ext.)
 
[57]
2025 | Konferenzbeitrag | FH-PUB-ID: 6203 | OA
Kaan A, Eris B, Halbrügge M, et al. AQ-Shuttle: Eine Studie über autonome Quartiers-Shuttle mit Mobilstation in Bielefeld. In: ; 2025:2-3. doi:10.60802/sidas.2025.2
HSBI-PUB | DOI | Download (ext.)
 
[56]
2025 | Konferenzbeitrag | FH-PUB-ID: 5976
Sanaullah S, Honda H, Roy K, Schneider A, Waßmuth J, Jungeblut T. Automating Neural Model Selection in Spiking Neural Networks Using AutoML Techniques*. In: 2025 22nd International Learning and Technology Conference (L&T). IEEE; 2025:274-279. doi:10.1109/LT64002.2025.10941536
HSBI-PUB | DOI
 
[55]
2025 | Artikel | FH-PUB-ID: 5366
Sanaullah S, Schneider A, Waßmuth J, Rückert U, Jungeblut T. RAVSim v2.0: Enhanced visualization and comparative analysis for neural network models. SoftwareX. 2025;29. doi:10.1016/j.softx.2024.102006
HSBI-PUB | DOI
 
[54]
2024 | Konferenzbeitrag | FH-PUB-ID: 5061 | OA
Ahmed QA, Sadeghi-Kohan S, Awais M, et al. RelaX: Reliability Assessment in Approximate Circuits. In: ; 2024.
HSBI-PUB | Dateien verfügbar | Download (ext.)
 
[53]
2024 | Konferenzbeitrag | FH-PUB-ID: 4782
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. A Spike Vision Approach for Multi-object Detection and Generating Dataset Using Multi-core Architecture on Edge Device. In: Iliadis L, Maglogiannis I, Papaleonidas A, Pimenidis E, Jayne C, eds. Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings. Communications in Computer and Information Science. Cham: Springer Nature Switzerland; 2024:317-328. doi:10.1007/978-3-031-62495-7_24
HSBI-PUB | DOI
 
[52]
2024 | Konferenzbeitrag | FH-PUB-ID: 5367 | OA
Koravuna S, Sanaullah S, Jungeblut T, Rückert U. Spiking Neural Network Models Analysis on Field Programmable Gate Arrays. In: Pudaruth S, Ogudo K, eds. International Conference on Intelligent and Innovative Computing Applications. Vol 2024. Society of Information Technologists and Engineers Ltd; 2024:259-270. doi:10.59200/ICONIC.2024.027
HSBI-PUB | DOI | Download (ext.)
 
[51]
2024 | Diskussionspapier | FH-PUB-ID: 5498
Hammer B, Alaçam Ö, Arlinghaus CS, et al. Sustainable Life-Cycle of Intelligent Socio-Technical Systems. Bielefeld University; 2024. doi:10.4119/UNIBI/2992602
HSBI-PUB | DOI
 
[50]
2024 | Konferenzbeitrag | FH-PUB-ID: 5336
Attaullah H, Kiani A, Jungeblut T. Improving Transfer Learning and Domain Adaptation in Smart Homes: The Role of Dynamic Domain Adaptation Layer. In: IEEE, ed. 2024 International Conference on Frontiers of Information Technology (FIT). IEEE; 2024:1-6. doi:10.1109/FIT63703.2024.10838396
HSBI-PUB | DOI
 
[49]
2024 | Konferenzbeitrag | FH-PUB-ID: 5315
Attaullah H, Sanaullah S, Jungeblut T. FL-DL: Fuzzy Logic with Deep Learning, Hybrid Anomaly Detection and Activity Prediction in Smart Homes Data-Sets. In: 2024 IEEE 24th International Symposium on Computational Intelligence and Informatics (CINTI). Budapest, Hungary: IEEE; 2024:43-48. doi:10.1109/CINTI63048.2024.10830825
HSBI-PUB | DOI
 
[48]
2024 | Konferenzbeitrag | FH-PUB-ID: 5098
Sanaullah S, Attaullah H, Jungeblut T. Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications. In: Omitaomu OA, Mostafavi A, Randhawa S, Niu H, eds. Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI. New York, NY, USA: ACM; 2024:50-53. doi:10.1145/3681780.3697244
HSBI-PUB | DOI
 
[47]
2024 | Konferenzbeitrag | FH-PUB-ID: 5097
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Advancements in Neural Network Generations. In: Kuhl U, DataNinja.nrw, eds. Proceedings of the SAIOnARA Conference. DataNinja sAIOnARA Conference; 2024. doi:10.11576/DATANINJA-1167
HSBI-PUB | DOI
 
[46]
2024 | Konferenzbeitrag | FH-PUB-ID: 5096
Sanaullah S, Attaullah H, Jungeblut T. Trade-offs Between Privacy and Performance in Encrypted Dataset using Machine Learning Models. In: Kuhl U, DataNinja.nrw, eds. Proceedings of the SAIOnARA Conference. DataNinja sAIOnARA Conference; 2024. doi:10.11576/DATANINJA-1166
HSBI-PUB | DOI
 
[45]
2024 | Artikel | FH-PUB-ID: 4997 | OA
Attaullah H, Sanaullah S, Jungeblut T. Analyzing Machine Learning Models for Activity Recognition Using Homomorphically Encrypted Real-World Smart Home Datasets: A Case Study. Applied Sciences. 2024;14(19). doi:10.3390/app14199047
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[44]
2024 | Kurzbeitrag Konferenz | FH-PUB-ID: 4883
Sanaullah S, Roy K, Ruckert U, Jungeblut T. Selection of Optimal Neural Model using Spiking Neural Network for Edge Computing  . In: IEEE, ed. 2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS). IEEE; 2024:1452-1453. doi:10.1109/ICDCS60910.2024.00147
HSBI-PUB | DOI | Inspire
 
[43]
2024 | Konferenzbeitrag | FH-PUB-ID: 4811
Sanaullah S, Attaullah H, Jungeblut T. The Next-Gen Interactive Runtime Simulator for Neural Network Programming. In: Söderberg E, Church L, eds. Companion Proceedings of the 8th International Conference on the Art, Science, and Engineering of Programming. New York, NY, USA: ACM; 2024:8-10. doi:10.1145/3660829.3660833
HSBI-PUB | DOI
 
[42]
2024 | Konferenzbeitrag | FH-PUB-ID: 4783 | OA
Sanaullah S, Roy K, Rückert U, Jungeblut T. A Hybrid Spiking-Convolutional Neural Network Approach for Advancing Machine Learning Models. In: Lutchyn T, Ramírez Rivera A, Ricaud B, eds. Proceedings of the 5th Northern Lights Deep Learning Conference. Vol 233. UiT The Arctic University, Tromsø, Norway: Proceedings of Machine Learning Research (PMLR); 2024. doi:10.48550/arXiv.2407.08861
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.) | WoS | arXiv
 
[41]
2024 | Kurzbeitrag Konferenz | FH-PUB-ID: 4639 | OA
Herzig TC, Marschner C, Held S, et al. KI-gestütztes Monitoring zur Unterstützung in der häuslichen Pflege (KIMUP) . In: Institute for Data Science Solutions, ed. Kongress KI@HSBI2023 Solutions im Fokus - Posterbeiträge . Vol 1. Kongress KI@HSBI2023 Solutions im Fokus - Posterbeiträge . Bielefeld: Hochschule Bielefeld; 2024:9-10. doi:10.60802/sidas.2024.1
HSBI-PUB | DOI | Download (ext.)
 
[40]
2023 | Buchbeitrag | FH-PUB-ID: 3222
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Streamlined Training of GCN for Node Classification with Automatic Loss Function and Optimizer Selection. In: Iliadis L, Maglogiannis I, Alonso S, Jayne C, Pimenidis E, eds. Engineering Applications of Neural Networks. 24th International Conference, EAAAI/EANN 2023, León, Spain, June 14–17, 2023, Proceedings. Communications in Computer and Information Science. Cham: Springer Nature Switzerland; 2023:191-202. doi:10.1007/978-3-031-34204-2_17
HSBI-PUB | DOI
 
[39]
2023 | Artikel | FH-PUB-ID: 3482 | OA
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Evaluation of Spiking Neural Nets-Based Image Classification Using the Runtime Simulator RAVSim. International Journal of Neural Systems. 2023. doi:10.1142/S0129065723500442
HSBI-PUB | DOI | Download (ext.)
 
[38]
2023 | Artikel | FH-PUB-ID: 3572 | OA
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications. Frontiers in Computational Neuroscience. 2023;17. doi:10.3389/fncom.2023.1215824
HSBI-PUB | DOI | Download (ext.)
 
[37]
2023 | Artikel | FH-PUB-ID: 3666
Koravuna S, Rückert U, Jungeblut T. Evaluating Spiking Neural Network Models: A Comparative Performance Analysis. Preprint. 2023. doi:10.13140/RG.2.2.21295.71847
HSBI-PUB | DOI
 
[36]
2023 | Artikel | FH-PUB-ID: 3665 | OA
Sanaullah S, Koravuna S, Ruckert U, Jungeblut T. Design-Space Exploration of SNN Models using Application-Specific Multi-Core Architectures. Preprint. 2023. doi:10.13140/RG.2.2.26328.88324
HSBI-PUB | DOI | Download (ext.)
 
[35]
2023 | Konferenzbeitrag | FH-PUB-ID: 3644 | OA
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Transforming Event-Based into Spike-Rate Datasets for Enhancing Neuronal Behavior Simulation to Bridging the Gap for SNNs. In: Paris France ; 2023. doi:10.13140/RG.2.2.14469.32485
HSBI-PUB | DOI | Download (ext.)
 
[34]
2023 | Konferenzbeitrag | FH-PUB-ID: 4207 | OA
Sanaullah S, Jungeblut T. Analysis of MR Images for Early and Accurate Detection of Brain Tumor using Resource Efficient Simulator Brain Analysis. In: New York USA; 2023. doi:10.5281/zenodo.10457930
HSBI-PUB | DOI | Download (ext.)
 
[33]
2023 | Kurzbeitrag Konferenz | FH-PUB-ID: 4206 | OA
Sanaullah S, Amanullah A, Roy K, Lee J-A, Chul-Jun S, Jungeblut T. A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting. In: ; 2023. doi:10.5281/zenodo.10458019
HSBI-PUB | DOI | Download (ext.)
 
[32]
2023 | Konferenzbeitrag | FH-PUB-ID: 4205 | OA
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. A Novel Spike Vision Approach for Robust Multi-Object Detection using SNNs. In: ; 2023. doi:10.5281/zenodo.10262228
HSBI-PUB | DOI | Download (ext.)
 
[31]
2023 | Konferenzbeitrag | FH-PUB-ID: 4208
Koravuna S, Sanaullah S, Jungeblut T, Rückert U. Digit Recognition Using Spiking Neural Networks on FPGA. In: Rojas I, Joya G, Catala A, eds. Advances in Computational Intelligence. 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, Ponta Delgada, Portugal, June 19–21, 2023, Proceedings, Part I. Lecture Notes in Computer Science. Cham: Springer Nature Switzerland; 2023:406-417. doi:10.1007/978-3-031-43085-5_32
HSBI-PUB | DOI
 
[30]
2022 | Konferenzbeitrag | FH-PUB-ID: 2757
Sanaullah S, Koravuna S, Jungeblut T, Rückert U. NireHApS: Neuro-Inspired and Resource-Efficient Hardware-Architectures for Plastic SNNs. In: ; 2022. doi:10.13140/RG.2.2.16202.85444
HSBI-PUB | DOI
 
[29]
2022 | Artikel | FH-PUB-ID: 4482 | OA
Baudisch J, Richter B, Jungeblut T. A Framework for Learning Event Sequences and Explaining Detected Anomalies in a Smart Home Environment. KI - Künstliche Intelligenz. 2022;36(3-4):259-266. doi:10.1007/s13218-022-00775-5
HSBI-PUB | Dateien verfügbar | DOI | Download (ext.)
 
[28]
2022 | Kurzbeitrag Konferenz | FH-PUB-ID: 2753
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. Real-Time Resource Efficient Simulator for SNNs-based Model Experimentation. 2022. doi:10.13140/RG.2.2.24761.85607
HSBI-PUB | DOI
 
[27]
2022 | Konferenzbeitrag | FH-PUB-ID: 3480 | OA
Sanaullah S, Koravuna S, Ruckert U, Jungeblut T. Real-Time SNNs Model Analyzing and Visualizing Experimentation. In: Unpublished; 2022. doi:10.13140/RG.2.2.14584.83201/1
HSBI-PUB | DOI | Download (ext.)
 
[26]
2022 | Konferenzbeitrag | FH-PUB-ID: 2276
Sanaullah S, Koravuna S, Rückert U, Jungeblut T. SNNs Model Analyzing and Visualizing Experimentation Using RAVSim. In: Iliadis L, Jayne C, Tefas A, Pimenidis E, eds. Engineering Applications of Neural Networks. 23rd International Conference, EAAAI/EANN 2022, Chersonissos, Crete, Greece, June 17–20, 2022, Proceedings. Communications in Computer and Information Science. Cham: Springer International Publishing; 2022:40-51. doi:10.1007/978-3-031-08223-8_4
HSBI-PUB | DOI
 
[25]
2019 | Konferenzbeitrag | FH-PUB-ID: 4483
Adams M, Ben-Salem S, Islam Z, et al. Towards an SSVEP-BCI Controlled Smart Home. In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE; 2019:2737-2742. doi:10.1109/SMC.2019.8914668
HSBI-PUB | DOI
 
[24]
2018 | Artikel | FH-PUB-ID: 4486
Ax J, Sievers G, Daberkow J, et al. CoreVA-MPSoC: A Many-Core Architecture with Tightly Coupled Shared and Local Data Memories. IEEE Transactions on Parallel and Distributed Systems. 2018;29(5):1030-1043. doi:10.1109/TPDS.2017.2785799
HSBI-PUB | DOI
 
[23]
2018 | Konferenzbeitrag | FH-PUB-ID: 4485
Gayen N, Ax J, Flasskamp M, et al. Scalable Mapping of Streaming Applications onto MPSoCs Using Optimistic Mixed Integer Linear Programming. In: 2018 26th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). IEEE; 2018:348-352. doi:10.1109/PDP2018.2018.00062
HSBI-PUB | DOI
 
[22]
2018 | Konferenzbeitrag | FH-PUB-ID: 4487
Cristal A, Unsal OS, Martorell X, et al. LEGaTO. In: Proceedings of the 15th ACM International Conference on Computing Frontiers. New York, NY, USA: ACM; 2018:276-278. doi:10.1145/3203217.3205339
HSBI-PUB | DOI
 
[21]
2018 | Konferenzbeitrag | FH-PUB-ID: 4484
Cristal A, Unsal OS, Martorell X, et al. LEGaTO. In: Proceedings of the 18th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation. New York, USA: ACM; 2018:210-217. doi:10.1145/3229631.3239370
HSBI-PUB | DOI
 
[20]
2017 | Buchbeitrag | FH-PUB-ID: 4490
Sievers G, Hübener B, Ax J, et al. The CoreVA-MPSoC: A Multiprocessor Platform for Software-Defined Radio. In: Hussain W, Nurmi J, Isoaho J, Garzia F, eds. Computing Platforms for Software-Defined Radio. Cham: Springer International Publishing; 2017:29-59. doi:10.1007/978-3-319-49679-5_3
HSBI-PUB | DOI
 
[19]
2017 | Konferenzbeitrag | FH-PUB-ID: 4489
Hesse M, Krause AF, Vogel L, et al. A connected chair as part of a smart home environment. In: 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks (BSN). IEEE; 2017:47-50. doi:10.1109/BSN.2017.7936004
HSBI-PUB | DOI
 
[18]
2017 | Konferenzbeitrag | FH-PUB-ID: 4488
Vohrmann M, Geisler P, Jungeblut T, Ruckert U. Design-space exploration of ultra-low power CMOS logic gates in a 28 nm FD-SOI technology. In: 2017 European Conference on Circuit Theory and Design (ECCTD). IEEE; 2017:1-4. doi:10.1109/ECCTD.2017.8093232
HSBI-PUB | DOI
 
[17]
2016 | Konferenzbeitrag | FH-PUB-ID: 4491
Flasskamp M, Sievers G, Ax J, et al. Performance estimation of streaming applications for hierarchical MPSoCs. In: Proceedings of the 2016 Workshop on Rapid Simulation and Performance Evaluation: Methods and Tools. New York, NY, USA: ACM; 2016:1-6. doi:10.1145/2852339.2852342
HSBI-PUB | DOI
 
[16]
2015 | Konferenzbeitrag | FH-PUB-ID: 4496
Ax J, Sievers G, Flasskamp M, Kelly W, Jungeblut T, Porrmann M. System-Level Analysis of Network Interfaces for Hierarchical MPSoCs. In: Proceedings of the 8th International Workshop on Network on Chip Architectures. New York, NY, USA: ACM; 2015:3-8. doi:10.1145/2835512.2835513
HSBI-PUB | DOI
 
[15]
2015 | Konferenzbeitrag | FH-PUB-ID: 4494
Sievers G, Ax J, Kucza N, et al. Evaluation of interconnect fabrics for an embedded MPSoC in 28 nm FD-SOI. In: 2015 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE; 2015:1925-1928. doi:10.1109/ISCAS.2015.7169049
HSBI-PUB | DOI
 
[14]
2015 | Konferenzbeitrag | FH-PUB-ID: 4493
Sievers G, Daberkow J, Ax J, et al. Comparison of Shared and Private L1 Data Memories for an Embedded MPSoC in 28nm FD-SOI. In: 2015 IEEE 9th International Symposium on Embedded Multicore/Many-Core Systems-on-Chip. IEEE; 2015:175-181. doi:10.1109/MCSoC.2015.25
HSBI-PUB | DOI
 
[13]
2015 | Konferenzbeitrag | FH-PUB-ID: 4492
Vohrmann M, Chatterjee S, Lutkemeier S, Jungeblut T, Porrmann M, Rückert U. A 65 nm standard cell library for ultra low-power applications. In: 2015 European Conference on Circuit Theory and Design (ECCTD). IEEE; 2015:1-4. doi:10.1109/ECCTD.2015.7300041
HSBI-PUB | DOI
 
[12]
2014 | Konferenzbeitrag | FH-PUB-ID: 4498
Hübener B, Sievers G, Jungeblut T, Porrmann M, Rückert U. CoreVA: A Configurable Resource-Efficient VLIW Processor Architecture. In: 2014 12th IEEE International Conference on Embedded and Ubiquitous Computing. IEEE; 2014:9-16. doi:10.1109/EUC.2014.11
HSBI-PUB | DOI
 
[11]
2014 | Konferenzbeitrag | FH-PUB-ID: 4497
Kelly W, Flasskamp M, Sievers G, et al. A communication model and partitioning algorithm for streaming applications for an embedded MPSoC. In: 2014 International Symposium on System-on-Chip (SoC). IEEE; 2014:1-6. doi:10.1109/ISSOC.2014.6972436
HSBI-PUB | DOI
 
[10]
2014 | Konferenzbeitrag | FH-PUB-ID: 4495
Keuck L, Hemmelgarn F, Fröhleke N, et al. Neuro control of a PFC rectifier for harmonic reduction at partial loads. In: 2014 International Conference on Advances in Green Energy (ICAGE). IEEE; 2014:94-99. doi:10.1109/ICAGE.2014.7050149
HSBI-PUB | DOI
 
[9]
2013 | Konferenzbeitrag | FH-PUB-ID: 4502
Christ P, Sievers G, Einhaus J, Jungeblut T, Porrmann M, Rückert U. Pareto-optimal signal processing on low-power microprocessors. In: 2013 IEEE SENSORS. IEEE; 2013:1-4. doi:10.1109/ICSENS.2013.6688593
HSBI-PUB | DOI
 
[8]
2013 | Konferenzbeitrag | FH-PUB-ID: 4501
Sievers G, Christ P, Einhaus J, Jungeblut T, Porrmann M, Rückert U. Design-space exploration of the configurable 32 bit VLIW processor CoreVA for signal processing applications. In: 2013 NORCHIP. IEEE; 2013:1-4. doi:10.1109/NORCHIP.2013.6702002
HSBI-PUB | DOI
 
[7]
2013 | Artikel | FH-PUB-ID: 4500
Jungeblut T, Hübener B, Porrmann M, Rückert U. A systematic approach for optimized bypass configurations for application-specific embedded processors. ACM Transactions on Embedded Computing Systems. 2013;13(2):1-25. doi:10.1145/2514641.2514645
HSBI-PUB | DOI
 
[6]
2013 | Artikel | FH-PUB-ID: 4499
Lütkemeier S, Jungeblut T, Berge HKO, Aunet S, Porrmann M, Rückert U. A 65 nm 32 b Subthreshold Processor With 9T Multi-Vt SRAM and Adaptive Supply Voltage Control. IEEE Journal of Solid-State Circuits. 2013;48(1):8-19. doi:10.1109/JSSC.2012.2220671
HSBI-PUB | DOI
 
[5]
2012 | Konferenzbeitrag | FH-PUB-ID: 4504
Jungeblut T, Ax J, Porrmann M, Rückert U. A TCMS-based architecture for GALS NoCs. In: 2012 IEEE International Symposium on Circuits and Systems. IEEE; 2012:2721-2724. doi:10.1109/ISCAS.2012.6271870
HSBI-PUB | DOI
 
[4]
2012 | Konferenzbeitrag | FH-PUB-ID: 4503
Luetkemeier S, Jungeblut T, Porrmann M, Rückert U. A 200mV 32b subthreshold processor with adaptive supply voltage control. In: 2012 IEEE International Solid-State Circuits Conference. IEEE; 2012:484-486. doi:10.1109/ISSCC.2012.6177101
HSBI-PUB | DOI
 
[3]
2010 | Artikel | FH-PUB-ID: 4506
Jungeblut T, Puttmann C, Dreesen R, et al. Resource efficiency of hardware extensions of a 4-issue VLIW processor for elliptic curve cryptography. Advances in Radio Science. 2010;8:295-305. doi:10.5194/ars-8-295-2010
HSBI-PUB | DOI
 
[2]
2010 | Konferenzbeitrag | FH-PUB-ID: 4505
Jungeblut T, Sievers G, Porrmann M, Rückert U. Design Space Exploration for Memory Subsystems of VLIW Architectures. In: 2010 IEEE Fifth International Conference on Networking, Architecture, and Storage. IEEE; 2010:377-385. doi:10.1109/NAS.2010.14
HSBI-PUB | DOI
 
[1]
2008 | Artikel | FH-PUB-ID: 4507
Jungeblut T, Grünewald M, Porrmann M, Rückert U. Realtime multiprocessor for mobile ad hoc networks. Advances in Radio Science. 2008;6:239-243. doi:10.5194/ars-6-239-2008
HSBI-PUB | DOI
 
Markierte Publikation(en)

Suche

Publikationen filtern

Darstellung / Sortierung

Zitationsstil: AMA

Export / Einbettung