StomachNet: Optimal Deep Learning Features Fusion for Stomach Abnormalities Classification

StomachNet: Optimal Deep Learning Features Fusion for Stomach Abnormalities Classification

A fully automated design is proposed in this work employing optimal deep learning features for classifying gastrointestinal infections. Here, three prominent infections– ulcer, bleeding, polyp and a healthy class are considered as class labels. In the initial stage, the contrast is improv...

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Bibliographic Details
Main Authors: Muhammad Attique Khan, Muhammad Shahzad Sarfraz, Majed Alhaisoni, Abdulaziz A. Albesher, Shuihua Wang, Imran Ashraf
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Stomach infections
contrast stretching
deep learning
optimization
fusion
Online Access:https://ieeexplore.ieee.org/document/9240940/

Internet

https://ieeexplore.ieee.org/document/9240940/

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