---
res:
  bibo_abstract:
  - '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.@eng'
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Viktoriia
      foaf_name: Vovchenko, Viktoriia
      foaf_surname: Vovchenko
      foaf_workInfoHomepage: http://www.librecat.org/personId=252442
    orcid: 0009-0004-9798-1112
    orcid_put_code_url: https://api.orcid.org/v2.0/0009-0004-9798-1112/work/218229773
  - foaf_Person:
      foaf_givenName: Sergej
      foaf_name: Schultenkämper, Sergej
      foaf_surname: Schultenkämper
      foaf_workInfoHomepage: http://www.librecat.org/personId=236164
    orcid: 0009-0005-6858-9813
    orcid_put_code_url: https://api.orcid.org/v2.0/0009-0005-6858-9813/work/218229775
  - foaf_Person:
      foaf_givenName: Frederik
      foaf_name: Bäumer, Frederik
      foaf_surname: Bäumer
      foaf_workInfoHomepage: http://www.librecat.org/personId=241734
    orcid: 0000-0002-0826-0144
    orcid_put_code_url: https://api.orcid.org/v2.0/0000-0002-0826-0144/work/218229776
  dct_date: 2026^xs_gYear
  dct_language: eng
  dct_publisher: IARIA@
  dct_subject:
  - segmentation
  - model comparison
  - face parsing
  dct_title: A Web-Based Platform for Interactive Comparison of Neural Network Image
    Segmentation Models@
...