GIT-Net: An Ensemble Deep Learning-Based GI Tract Classification of Endoscopic Images

GIT-Net: An Ensemble Deep Learning-Based GI Tract Classification of Endoscopic Images

This paper presents an ensemble of pre-trained models for the accurate classification of endoscopic images associated with Gastrointestinal (GI) diseases and illnesses. In this paper, we propose a weighted average ensemble model called GIT-NET to classify GI-tract diseases. We evaluated the model on...

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Bibliographic Details
Main Authors: Hemalatha Gunasekaran, Krishnamoorthi Ramalakshmi, Deepa Kanmani Swaminathan, Andrew J, Manuel Mazzara
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Bioengineering
Subjects:
ensemble learning
base learners
gastrointestinal tract
deep learning
transfer learning
Online Access:https://www.mdpi.com/2306-5354/10/7/809

Internet

https://www.mdpi.com/2306-5354/10/7/809

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