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https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#一动机篇
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#二cnn-卷积层篇
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#21-卷积层的本质是什么
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#22-cnn-卷积层与全连接层的联系
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#23-channel的含义是什么
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/20180404135638186.png
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/20180404113714719.png
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/20180404150134375.png
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#三cnn-池化层篇
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#31-池化层针对区域是什么
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#32-池化层的种类有哪些
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#33-池化层的作用是什么
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#34-池化层-反向传播-是什么样的
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#35-mean-pooling-池化层-反向传播-是什么样的
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/20210105193358.png
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#36-max-pooling-池化层-反向传播-是什么样的
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/20210105193728.png
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#四cnn-整体篇
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#41-cnn-的流程是什么
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#42-cnn-的特点是什么
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#43-卷积神经网络为什么会具有平移不变性
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#44-卷积神经网络中im2col是如何实现的
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/2021-01-06-16-16-19.png
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/2021-01-06-16-16-50.png
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/2021-01-06-16-21-27.png
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/2021-01-06-16-22-53.png
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/2021-01-06-16-29-17.png
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/2021-01-06-16-25-42.png
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/2021-01-06-16-30-53.png
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/2021-01-06-16-37-37.png
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#45-cnn-的局限性是什么
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#五iterated-dilated-cnn-篇
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#51-什么是-dilated-cnn-空洞卷积
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/1610177872501.png
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/cnn-dilation-in_7_out_3.gif
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#52-什么是-iterated-dilated-cnn
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#六反卷积-篇
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#61-解释反卷积的原理和用途
https://github.com/caobinbc/NLP-Interview-Notes/blob/main/DeepLearningAlgorithm/cnn/img/pr16808o61q24973o42q7rsqq88os391.jpg
https://camo.githubusercontent.com/b63d586148a6444204e2c5690e0f8c42380de80dd8bc0d8c35980c9d17a33a9b/68747470733a2f2f69322e6b6b6e6577732e63632f5349473d327374667567352f6374702d767a6e74722f713072306e36383872707337343832326f726e6e3538393538727172723472312e6a7067
https://kknews.cc/code/zb2jr43.htmlhttps://kknews.cc/code/zb2jr43.html
https://zhuanlan.zhihu.com/p/48501100https://zhuanlan.zhihu.com/p/48501100
https://github.com/caobinbc/NLP-Interview-Notes/tree/main/DeepLearningAlgorithm/cnn#参考
理解为什么要将全连接层转化为卷积层https://www.cnblogs.com/liuzhan709/p/9356960.html
What do the fully connected layers do in CNNs?https://stats.stackexchange.com/questions/182102/what-do-the-fully-connected-layers-do-in-cnns?utm_medium=organic&utm_source=google_rich_qa&utm_campaign=google_rich_qa
CNN全连接层和卷积层的转化https://blog.csdn.net/weixin_43199584/article/details/105125620
【CNN】理解卷积神经网络中的通道 channelhttps://blog.csdn.net/sscc_learning/article/details/79814146
万字长文概述NLP中的深度学习技术https://www.linkresearcher.com/information/6c7a15b5-236a-40f3-879f-af2ac06c2557
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