Enhanced DL-Based Breast Cancer Diagnosis and Classification Using Modified DenseNet-121, DenseNet-201, and MobileNetV2: Optimized Architectures and Refined Activation Functions
Deep learning has revolutionized medical image analysis, particularly in the domain of breast cancer detection. Despite notable progress, further optimization of neural network architectures and activation functions remains critical for enhancing classification accuracy and model generalization. Thi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11106463/ |
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