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Knowledge Distillation of Vision Transformers and Convolutional Networks to Predict Inflammatory Bowel Disease

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Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (CIARP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14469))

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Abstract

Inflammatory bowel disease is a chronic disease of unknown cause that can affect the entire gastrointestinal tract, from the mouth to the anus. It is important for patients with this pathology that a good diagnosis is made as early as possible, so that the inflammation present in the mucosa intestinal is controlled and the most severe symptoms are reduced, thus offering the quality of life to people. Therefore, through this comparative study, we seek to find a way of automating the diagnosis of these patients during the endoscopic examination, reducing the subjectivity that is subject to the observation of a gastroenterologist, using six CNNs: AlexNet, ResNet50, VGG16, ResNet50-MobileNetV2 and Hybrid model. Also, five ViTs were used in this study: ViT-B/32, ViT-S/32, ViT-B/16, ViT-S/16 and R26+S/32. This comparison also consists in applying knowledge distillation to build simpler models, with fewer parameters, based on the learning of the pre-trained architectures on large volumes of data. It is concluded that in the ViTs framework, it is possible to reduce 25x the number of parameters by maintaining good performance and reducing the inference time by 5.32 s. For CNNs the results show that it is possible to reduce 107x the number of parameters, reducing consequently the inference time in 3.84 s.

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Author information

Authors and Affiliations

  1. Instituto Politécnico de Coimbra, Instituto Superior de Engenharia, Rua Pedro Nunes - Quinta da Nora, 3030-199, Coimbra, Portugal

    José Maurício & Inês Domingues

  2. Centro de Investigação do Instituto Português de Oncologia do Porto (CI-IPOP): Grupo de Física Médica, Radiobiologia e Protecção Radiológica, Coimbra, Portugal

    Inês Domingues

Authors
  1. José Maurício
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  2. Inês Domingues
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Correspondence to José Maurício .

Editor information

Editors and Affiliations

  1. Polytechnic Institute of Coimbra, Coimbra Institute of Engineering, Coimbra, Portugal

    Verónica Vasconcelos

  2. Polytechnic Institute of Coimbra, Coimbra Institute of Engineering, Coimbra, Portugal

    Inês Domingues

  3. Polytechnic Institute of Coimbra, Coimbra Institute of Engineering, Coimbra, Portugal

    Simão Paredes

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Maurício, J., Domingues, I. (2024). Knowledge Distillation of Vision Transformers and Convolutional Networks to Predict Inflammatory Bowel Disease. In: Vasconcelos, V., Domingues, I., Paredes, S. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2023. Lecture Notes in Computer Science, vol 14469. Springer, Cham. https://doi.org/10.1007/978-3-031-49018-7_27

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  • DOI: https://doi.org/10.1007/978-3-031-49018-7_27

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