Distilling the knowledge in CNN for WCE screening tool - Sorbonne Université Access content directly
Conference Papers Year : 2019

Distilling the knowledge in CNN for WCE screening tool

Thomas Garbay
  • Function : Author
  • PersonId : 1049244
Orlando Chuquimia
  • Function : Author
  • PersonId : 1049243
Andrea Pinna
  • Function : Author
  • PersonId : 955698
Hichem Sahbi
Xavier Dray
  • Function : Author
  • PersonId : 1004293
Bertrand Granado

Abstract

A way to improve the early detection of colorectal cancer is screening. Polyps are a marker of colorectal cancer and the best modality to detect them is the image. In 2003 Wireless Capsule Endoscopy was introduced and opened a way to integrate automatic image processing to realize a screening tool. Moreover, the capacity to detect polyp with Convolutional Neural Network was shown in many scientific studies, but one issue is the integration of these networks. In this article, we present our works to integrate CNN or image processing based on a CNN inside a WCE to realize a powerful screening tool. We apply the knowledge distillation method. We prove that knowledge distillation is efficient from VGG16 to Squeezenet in polyp detection context
Fichier principal
Vignette du fichier
DASIP2019.pdf (232.16 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-03467026 , version 1 (06-12-2021)

Identifiers

Cite

Thomas Garbay, Orlando Chuquimia, Andrea Pinna, Hichem Sahbi, Xavier Dray, et al.. Distilling the knowledge in CNN for WCE screening tool. 2019 Conference on Design and Architectures for Signal and Image Processing (DASIP), Oct 2019, Montreal, Canada. pp.19-22, ⟨10.1109/DASIP48288.2019.9049201⟩. ⟨hal-03467026⟩
36 View
91 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More