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Nizza, Frankreich: IARIA.","bibtex":"@inproceedings{Vovchenko_Schultenkämper_Bäumer, title={A Web-Based Platform for Interactive Comparison of Neural Network Image Segmentation Models}, booktitle={2026 The Second International Conference on AI-based Media Innovation}, publisher={IARIA}, author={Vovchenko, Viktoriia and Schultenkämper, Sergej and Bäumer, Frederik} }","alphadin":"Vovchenko, Viktoriia ; Schultenkämper, Sergej ; Bäumer, Frederik: A Web-Based Platform for Interactive Comparison of Neural Network Image Segmentation Models. In: 2026 The Second International Conference on AI-based Media Innovation : IARIA","ieee":"V. Vovchenko, S. Schultenkämper, and F. Bäumer, “A Web-Based Platform for Interactive Comparison of Neural Network Image Segmentation Models,” in 2026 The Second International Conference on AI-based Media Innovation, Nizza, Frankreich.","ama":"Vovchenko V, Schultenkämper S, Bäumer F. 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Bäumer, in: 2026 The Second International Conference on AI-Based Media Innovation, IARIA, n.d."},"status":"public","conference":{"name":"2026 The Second International Conference on AI-based Media Innovation","location":"Nizza, Frankreich","start_date":"2026-07-05","end_date":"2026-07-09"},"date_updated":"2026-06-22T08:25:46Z","publisher":"IARIA","_id":"7002","year":"2026","language":[{"iso":"eng"}],"abstract":[{"text":"Selecting an appropriate semantic segmentation model for a given application domain remains a challenging and time-consuming task for practitioners and researchers. This paper presents an interactive, web-based platform that enables side-by-side visual comparison of multiple neural network segmentation models applied to identical images. The system integrates three transformer-based segmentation models: a face-parsing network producing 19 semantic classes, a SegFormer-B3 clothing segmentation model with 18 classes, and a Mask2Former model for general-purpose scene segmentation spanning 150 ADE20K categories. Key contributions include side-by-side evaluation of model outputs across multiple architectures and image categories, with real-time segment highlighting and a scalable inference caching system that enables model comparisons without requiring repeated graphics processing unit (GPU) computation. The platform organizes a curated dataset of images under a hierarchical category taxonomy, supporting structured evaluation across demographic and contextual variables. As a practical use case, the system is applied within the ADRIAN project to assist in verifying identity consistency across images through segmentation-based analysis. The platform thus contributes a specialized artificial intelligence (AI) tool for systematic segmentation and object detection model evaluation within media analysis pipelines, where selecting appropriate models is a recurring challenge across tasks from identity verification to content moderation. It is available under https://github.com/vika-v-v/neural-networks-for-image-segmentation and designed to lower the barrier for comparative model evaluation in applied computer vision workflows.","lang":"eng"}],"date_created":"2026-06-19T16:31:47Z","title":"A Web-Based Platform for Interactive Comparison of Neural Network Image Segmentation Models","type":"conference","user_id":"220548","keyword":["segmentation","model comparison","face parsing"],"publication_status":"accepted","publication":"2026 The Second International Conference on AI-based Media Innovation"},{"language":[{"iso":"eng"}],"year":"2026","_id":"6998","date_updated":"2026-06-22T07:54:10Z","conference":{"name":"2026 The First International Conference on Security and Cybersecurity in the AI and Digital Context","location":"Porto, Portugal","start_date":"2026-06-05","end_date":"2026-06-11"},"status":"public","author":[{"first_name":"Viktoriia","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0004-9798-1112/work/218229244","id":"252442","last_name":"Vovchenko","orcid":"0009-0004-9798-1112","full_name":"Vovchenko, Viktoriia"},{"full_name":"Barberi, Vincenzo","last_name":"Barberi","first_name":"Vincenzo"},{"id":"236164","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0005-6858-9813/work/218229246","first_name":"Sergej","full_name":"Schultenkämper, Sergej","orcid":"0009-0005-6858-9813","last_name":"Schultenkämper"},{"orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-0826-0144/work/218229247","id":"241734","first_name":"Frederik","full_name":"Bäumer, Frederik","orcid":"0000-0002-0826-0144","last_name":"Bäumer"}],"citation":{"alphadin":"Vovchenko, Viktoriia ; Barberi, Vincenzo ; Schultenkämper, Sergej ; Bäumer, Frederik: ADRIAN InstructFace-Edit - Towards Robust Detection of AI-Manipulated Face Images. 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M. G., Eryılmaz, B., Becker, H., Idrissi-Yaghir, A., Schäfer, H., … Friedrich, C. M. (2024). WisPerMed at “Discharge Me!”: Advancing Text Generation in Healthcare with Large Language Models, Dynamic Expert Selection, and Priming Techniques on MIMIC-IV. In D. Demner-Fushman, S. Ananiadou, M. Miwa, K. Roberts, & J. Tsujii (Eds.), Proceedings of the 23rd Workshop on Biomedical Natural Language Processing (pp. 105–121). Stroudsburg, PA, USA: Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.bionlp-1.9","alphadin":"Damm, Hendrik ; Pakull, Tabea Margareta Grace ; Eryılmaz, Bahadır ; Becker, Helmut ; Idrissi-Yaghir, Ahmad ; Schäfer, Henning ; Schultenkämper, Sergej ; Friedrich, Christoph M.: WisPerMed at “Discharge Me!”: Advancing Text Generation in Healthcare with Large Language Models, Dynamic Expert Selection, and Priming Techniques on MIMIC-IV. In: Demner-Fushman, D. ; Ananiadou, S. ; Miwa, M. ; Roberts, K. ; Tsujii, J. 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