Convolutional Neural Networks for Breast Cancer Screening: Transfer Learning with Exponential Decay
arXiv:1711.10752
Abstract
In this paper, we propose a Computer Assisted Diagnosis (CAD) system based on a deep Convolutional Neural Network (CNN) model, to build an end-to-end learning process that classifies breast mass lesions. We investigate the impact that has transfer learning when large data is scarce, and explore the proper way to fine-tune the layers to learn features that are more specific to the new data. The proposed approach showed better performance compared to other proposals that classified the same dataset.
6 pages, 2 figures, NIPS ML4H 2017: Machine Learning for Health Workshop at NIPS 2017, Long Beach, CA, United States, December 8, 2017