Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection

Volume: 83, Issue: 5, Pages: 562 - 576
Published: Jan 27, 2020
Abstract
Automated detection and classification of gastric infections (i.e., ulcer, polyp, esophagitis, and bleeding) through wireless capsule endoscopy (WCE) is still a key challenge. Doctors can identify these endoscopic diseases by using the computer-aided diagnostic (CAD) systems. In this article, a new fully automated system is proposed for the recognition of gastric infections through multi-type features extraction, fusion, and robust features...
Paper Details
Title
Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection
Published Date
Jan 27, 2020
Volume
83
Issue
5
Pages
562 - 576
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