Curriculum Incremental Deep Learning on BreakHis DataSet

Author:

MAYOUF MOUNA SABRINE1,DUPIN DE SAINT-Cyr FLORENCE1

Affiliation:

1. IRIT LABORATORY, TOULOUSE, PAUL SABATIER UNIVERSITY, TOULOUSE, France

Publisher

ACM

Reference40 articles.

1. Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural Network

2. Jose  F Arocha , Dongwen Wang , and Vimla  L Patel . 2005. Identifying reasoning strategies in medical decision making: a methodological guide. J. of biomedical informatics 38, 2 ( 2005 ), 154–171. https://doi.org/10.1016/j.jbi.2005.02.001. Jose F Arocha, Dongwen Wang, and Vimla L Patel. 2005. Identifying reasoning strategies in medical decision making: a methodological guide. J. of biomedical informatics 38, 2 (2005), 154–171. https://doi.org/10.1016/j.jbi.2005.02.001.

3. Classification of Breast Cancer Based on Histology Images Using Convolutional Neural Networks

4. Neslihan Bayramoglu , Juho Kannala , and Janne Heikkilä . 2016 . Deep learning for magnification independent breast cancer histopathology image classification . In 2016 23rd International conference on pattern recognition (ICPR). IEEE, 2440–2445 . https://doi.org/10.1109/ICPR.2016.7900002. Neslihan Bayramoglu, Juho Kannala, and Janne Heikkilä. 2016. Deep learning for magnification independent breast cancer histopathology image classification. In 2016 23rd International conference on pattern recognition (ICPR). IEEE, 2440–2445. https://doi.org/10.1109/ICPR.2016.7900002.

5. Curriculum learning

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