Machine learning
AlexNet
AlexNet是由Alex Krizhevsky、Ilya Sutskever和Geoffrey Hinton于2012年推出的一种深度卷积神经网络（CNN）。它以15.3%的top-5错误率赢得了ImageNet大规模视觉识别挑战赛（ILSVRC 2012），领先亚军超过10个百分点，重新点燃了人们对深度学习的广泛兴趣。该架构引入或普及了几种技术——ReLU激活、Dropout正则化和多GPU训练——这些技术已成为该领域的标准实践。
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来源
- Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). ImageNet Classification with Deep Convolutional Neural Networks. Advances in Neural Information Processing Systems, 25, 1097–1105. (Republished: Communications of the ACM, 60(6), 84–90, 2017.) DOI: 10.1145/3065386 ↗
- Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning (Ch. 9: Convolutional Networks). MIT Press. ISBN: 978-0-262-03561-3
- LeCun, Y., Bengio, Y., & Hinton, G. E. (2015). Deep Learning. Nature, 521, 436–444. DOI: 10.1038/nature14539 ↗
如何引用本页
ScholarGate. (2026, June 3). AlexNet (Krizhevsky–Sutskever–Hinton Deep Convolutional Neural Network). ScholarGate. https://scholargate.app/zh/deep-learning/alexnet
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