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Работы, на которые ссылается эта работа
Работ: 46
Работа: Bridging the gap between Natural and Medical Images through Deep Colorization
Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren +1
Статья2016Цитирований: 61ABIU-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger, Philipp Fischer, Thomas Brox
Глава2015Цитирований: 32ABIControlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Yoav Benjamini, Yosef Hochberg
Статья1995Цитирований: 20ABIA survey on deep learning in medical image analysis
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi +6
Обзорная статья2017Цитирований: 16ABIDensely Connected Convolutional Networks
Gao Huang, Zhuang Liu, Laurens van der Maaten +1
Препринт2017Цитирований: 13ABIImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su +9
Статья2015Цитирований: 11ABIMastering the game of Go with deep neural networks and tree search
David Silver, Aja Huang, Chris J. Maddison +17
Статья2016Цитирований: 5ABIConvolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
Nima Tajbakhsh, J. Shin, Suryakanth Gurudu +4
Статья2016Цитирований: 3ABICheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
Jeremy Irvin, Pranav Rajpurkar, Michael Ko +17
Статья2019Цитирований: 2ABIHyperspectral Remote Sensing Data Analysis and Future Challenges
José M. Bioucas‐Dias, Antonio Plaza, Gustau Camps‐Valls +3
Статья2013Цитирований: 2ABIMURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs
Pranav Rajpurkar, Jeremy Irvin, Aarti Bagul +11
Препринт2017Цитирований: 2ABI