Multi-Domain Feature Incorporation of Lightweight Convolutional Neural Networks and Handcrafted Features for Lung and Colon Cancer Diagnosis

This study presents a computer-aided diagnostic (CAD) framework that integrates multi-domain features through a hybrid methodology. The system uses several light deep networks (EfficientNetB0, MobileNet, and ResNet-18), which feature fewer layers and parameters, unlike traditional systems that depen...

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Bibliographic Details
Main Author:	Omneya Attallah
Format:	Article
Language:	English
Published:	MDPI AG 2025-04-01
Series:	Technologies
Subjects:	medical image analysis convolutional neural networks gray-level co-occurrence matrix local binary pattern feature fusion feature selection
Online Access:	https://www.mdpi.com/2227-7080/13/5/173
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Multi-Domain Feature Incorporation of Lightweight Convolutional Neural Networks and Handcrafted Features for Lung and Colon Cancer Diagnosis

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