LeNet

LeNet is a series of convolutional neural network structure proposed by LeCun et al..^[1] The earliest version, LeNet-1, was trained in 1989. In general, when "LeNet" is referred to without a number, it refers to LeNet-5 (1998), the most well-known version.

Convolutional neural networks are a kind of feed-forward neural network whose artificial neurons can respond to a part of the surrounding cells in the coverage range and perform well in large-scale image processing. LeNet-5 was one of the earliest convolutional neural networks and was historically important during the development of deep learning.^[2]

^ Lecun, Y.; Bottou, L.; Bengio, Y.; Haffner, P. (1998). "Gradient-based learning applied to document recognition" (PDF). Proceedings of the IEEE. 86 (11): 2278–2324. doi:10.1109/5.726791. S2CID 14542261.
^ Zhang, Aston; Lipton, Zachary; Li, Mu; Smola, Alexander J. (2024). "7.6. Convolutional Neural Networks (LeNet)". Dive into deep learning. Cambridge New York Port Melbourne New Delhi Singapore: Cambridge University Press. ISBN 978-1-009-38943-3.

[:1-1] Lecun, Y.; Bottou, L.; Bengio, Y.; Haffner, P. (1998). "Gradient-based learning applied to document recognition" (PDF). Proceedings of the IEEE. 86 (11): 2278–2324. doi:10.1109/5.726791. S2CID 14542261.

[2] Zhang, Aston; Lipton, Zachary; Li, Mu; Smola, Alexander J. (2024). "7.6. Convolutional Neural Networks (LeNet)". Dive into deep learning. Cambridge New York Port Melbourne New Delhi Singapore: Cambridge University Press. ISBN 978-1-009-38943-3.

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LeNet

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