B2C3NetF2: Breast cancer classification using an end‐to‐end deep learning feature fusion and satin bowerbird optimization controlled Newton Raphson feature selection

B2C3NetF2: Breast cancer classification using an end‐to‐end deep learning feature fusion and satin bowerbird optimization controlled Newton Raphson feature selection

Abstract Currently, the improvement in AI is mainly related to deep learning techniques that are employed for the classification, identification, and quantification of patterns in clinical images. The deep learning models show more remarkable performance than the traditional methods for medical imag...

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Bibliographic Details
Main Authors: Mamuna Fatima, Muhammad Attique Khan, Saima Shaheen, Nouf Abdullah Almujally, Shui‐Hua Wang
Format: Article
Language:English
Published: Wiley 2023-12-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
artificial intelligence
artificial neural network
deep learning
medical image processing
multi‐objective optimization
Online Access:https://doi.org/10.1049/cit2.12219

Internet

https://doi.org/10.1049/cit2.12219

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