Evaluation of Learning Approaches Based on Convolutional Neural Networks for Mammogram Classification

Author:

Arias Roberto,Narváez Fabián,Franco Hugo

Publisher

Springer International Publishing

Reference45 articles.

1. Abdelhafiz, D., Yang, C., Ammar, R., Nabavi, S.: Deep convolutional neural networks for mammography: advances, challenges and applications. BMC Bioinformatics 20(11), 281 (2019)

2. Bai, L., Zhao, Y., Huang, X.: A CNN accelerator on FPGA using depthwise separable convolution. IEEE Trans. Circuits Syst. II Express Briefs 65(10), 1415–1419 (2018)

3. Basanth, M., Shettar, R.: Transfer learning on pre-trained deep convolutional neural network for classification of masses in mammograms. IOSR J. Comput. Eng. 19(50), e5 (2017)

4. Bendersky, E.: Depthwise separable convolutions for machine learning (2019). https://eli.thegreenplace.net/2018/depthwise-separable-convolutions-for-machine-learning/

5. Lecture Notes in Computer Science;Y Bengio,2012

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