Convolutional Neural Networks for Breast Cancer Screening: Transfer Learning with Exponential Decay

Autor:	Chougrad, Hiba, Zouaki, Hamid, Alheyane, Omar
Rok vydání:	2017
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	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. Comment: 6 pages, 2 figures, NIPS ML4H 2017: Machine Learning for Health Workshop at NIPS 2017, Long Beach, CA, United States, December 8, 2017
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1711.10752 Zobrazit plný text záznamu View this record from Arxiv