[{"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"}],"publication_identifier":{"isbn":["978-1-68558-403-0"]},"user_id":"252442","publication_status":"accepted","date_created":"2026-06-19T16:31:47Z","publication":"2026 The Second International Conference on AI-based Media Innovation","date_updated":"2026-09-21T14:54:44Z","status":"public","editor":[{"last_name":"Böhm","first_name":"Stephan","full_name":"Böhm, Stephan"},{"full_name":"Ahrweiler, Petra","last_name":"Ahrweiler","first_name":"Petra"},{"full_name":"Gutenberg, Johannes","last_name":"Gutenberg","first_name":"Johannes"},{"full_name":"Leung, Clement ","first_name":"Clement ","last_name":"Leung"}],"author":[{"id":"252442","full_name":"Vovchenko, Viktoriia","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0004-9798-1112/work/218229773","orcid":"0009-0004-9798-1112","last_name":"Vovchenko","first_name":"Viktoriia"},{"first_name":"Sergej","orcid":"0009-0005-6858-9813","last_name":"Schultenkämper","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0005-6858-9813/work/218229775","full_name":"Schultenkämper, Sergej","id":"236164"},{"id":"241734","orcid":"0000-0002-0826-0144","last_name":"Bäumer","first_name":"Frederik","full_name":"Bäumer, Frederik","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-0826-0144/work/218229776"}],"citation":{"apa":"Vovchenko, V., Schultenkämper, S., &#38; Bäumer, F. (n.d.). A Web-Based Platform for Interactive Comparison of Neural Network Image Segmentation Models. In S. Böhm, P. Ahrweiler, J. Gutenberg, &#38; C. Leung (Eds.), <i>2026 The Second International Conference on AI-based Media Innovation</i>. Nizza, Frankreich: IARIA.","chicago":"Vovchenko, Viktoriia, Sergej Schultenkämper, and Frederik Bäumer. “A Web-Based Platform for Interactive Comparison of Neural Network Image Segmentation Models.” In <i>2026 The Second International Conference on AI-Based Media Innovation</i>, edited by Stephan Böhm, Petra Ahrweiler, Johannes Gutenberg, and Clement  Leung. IARIA, n.d.","short":"V. Vovchenko, S. Schultenkämper, F. Bäumer, in: S. Böhm, P. Ahrweiler, J. Gutenberg, C. Leung (Eds.), 2026 The Second International Conference on AI-Based Media Innovation, IARIA, n.d.","alphadin":"<span style=\"font-variant:small-caps;\">Vovchenko, Viktoriia</span> ; <span style=\"font-variant:small-caps;\">Schultenkämper, Sergej</span> ; <span style=\"font-variant:small-caps;\">Bäumer, Frederik</span>: A Web-Based Platform for Interactive Comparison of Neural Network Image Segmentation Models. In: <span style=\"font-variant:small-caps;\">Böhm, S.</span> ; <span style=\"font-variant:small-caps;\">Ahrweiler, P.</span> ; <span style=\"font-variant:small-caps;\">Gutenberg, J.</span> ; <span style=\"font-variant:small-caps;\">Leung, C.</span> (Hrsg.): <i>2026 The Second International Conference on AI-based Media Innovation</i> : IARIA","ieee":"V. Vovchenko, S. Schultenkämper, and F. Bäumer, “A Web-Based Platform for Interactive Comparison of Neural Network Image Segmentation Models,” in <i>2026 The Second International Conference on AI-based Media Innovation</i>, Nizza, Frankreich.","mla":"Vovchenko, Viktoriia, et al. “A Web-Based Platform for Interactive Comparison of Neural Network Image Segmentation Models.” <i>2026 The Second International Conference on AI-Based Media Innovation</i>, edited by Stephan Böhm et al., 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}, editor={Böhm, Stephan and Ahrweiler, Petra and Gutenberg, Johannes and Leung, Clement Editors} }","ama":"Vovchenko V, Schultenkämper S, Bäumer F. 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