Automated Detection of Gastrointestinal Diseases Using Resnet50*-Based Explainable Deep Feature Engineering Model with Endoscopy Images

Automated Detection of Gastrointestinal Diseases Using Resnet50*-Based Explainable Deep Feature Engineering Model with Endoscopy Images

This work aims to develop a novel convolutional neural network (CNN) named ResNet50* to detect various gastrointestinal diseases using a new ResNet50*-based deep feature engineering model with endoscopy images. The novelty of this work is the development of ResNet50*, a new variant of the ResNet mod...

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Bibliographic Details
Main Authors: Veysel Yusuf Cambay, Prabal Datta Barua, Abdul Hafeez Baig, Sengul Dogan, Mehmet Baygin, Turker Tuncer, U. R. Acharya
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Sensors
Subjects:
ResNet50*
colon disease classification
deep feature engineering
multiple iterative feature selection
Online Access:https://www.mdpi.com/1424-8220/24/23/7710
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https://www.mdpi.com/1424-8220/24/23/7710

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