Optimization of ReLU Activation Function for Deep-Learning-based Breast Cancer Classification on Mammogram Images-Reference-Cited by-同舟云学术

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Optimization of ReLU Activation Function for Deep-Learning-based Breast Cancer Classification on Mammogram Images

Published:2024-06-29 Issue: Volume:83 Page:267-272
ISSN:
Container-title:2024 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)
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Author:

Razali Noor Fadzilah¹,Isa Iza Sazanita¹,Sulaiman Siti Noraini¹,Osman Muhammad Khusairi¹,Karim Noor Khairiah A.²,Nordin Siti Aminah³

Affiliation:

1. Universiti Teknologi MARA, Permatang Pauh Campus,Electrical Engineering Studies College of Engineering,Pulau Pinang,Malaysia

2. Universiti Sains Malaysia Bertam,Department of Biomedical Imaging, Advanced Medical and Dental Institute,Pulau Pinang,Malaysia

3. Universiti Teknologi MARA, Pasir Gudang Campus,Electrical Engineering Studies College of Engineering,Johor,Malaysia

Funder

Universiti Teknologi MARA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649806/10649618/10649623.pdf?arnumber=10649623

Reference32 articles.

1. Cancer statistics, 2022

2. Early Stage Breast Cancer Detection System using GLCM feature extraction and K-Nearest Neighbor (k-NN) on Mammography image

3. Towards feature selection for digital mammogram classification

4. A novel deep learning architecture outperforming ‘off‑the‑shelf’ transfer learning and feature‑based methods in the automated assessment of mammographic breast density

5. Breast Cancer Classification Using FCN and Beta Wavelet Autoencoder

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