Flexible, High Performance Convolutional Neural Networks for Image Classification
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 1237-1241.
Abstract
We present a fast, fully parameterizable GPU implementation of Convolutional Neural Network variants. Our feature extractors are neither carefully designed nor pre-wired, but rather learned in a supervised way. Our deep hierarchical architectures achieve the best published results on benchmarks for object classification (NORB, CIFAR10) and handwritten digit recognition (MNIST), with error rates of 2.53%, 19.51%, 0.35%, respectively. Deep nets trained by simple back-propagation perform better than more shallow ones. Learning is surprisingly rapid. NORB is completely trained within five epochs. Test error rates on MNIST drop to 2.42%, 0.97% and 0.48% after 1, 3 and 17 epochs, respectively.
@inproceedings{ijcai2011p210,
title = {Flexible, High Performance Convolutional Neural Networks for Image Classification},
author = {Ciresan, Dan Claudiu and Meier, Ueli and Masci, Jonathan and Gambardella, Luca Maria and Schmidhuber, Jürgen},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {1237--1241},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-210},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-210},
}
TY - CPAPER TI - Flexible, High Performance Convolutional Neural Networks for Image Classification AU - Ciresan, Dan Claudiu AU - Meier, Ueli AU - Masci, Jonathan AU - Gambardella, Luca Maria AU - Schmidhuber, Jürgen T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 1237 EP - 1241 DO - 10.5591/978-1-57735-516-8/IJCAI11-210 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-210 ER -Copied
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