关于RGB图像通道的意义:
https://zhuanlan.zhihu.com/p/369907785
最大池化、平均池化、自适应平均池化:
https://blog.csdn.net/qq_38737428/article/details/121523145
https://blog.csdn.net/qq_38737428/article/details/121780217
Sequential的用法:
https://blog.csdn.net/qq_27825451/article/details/90551513
view函数的使用:
https://blog.csdn.net/qq_26400705/article/details/109816853
SENet的代码手把手讲解:
https://www.bilibili.com/video/BV1rL4y1n7p3/?p=2&spm_id_from=pageDriver&vd_source=7cf48963f4df908b54a5dae7bb14180e
CBAM(空间注意力和通道注意力):
https://www.bilibili.com/video/BV1rL4y1n7p3/?p=3&vd_source=7cf48963f4df908b54a5dae7bb14180e
torch.max函数的用法:
https://blog.csdn.net/ViatorSun/article/details/108909312
torch.cat函数的用法:
https://blog.csdn.net/xinjieyuan/article/details/105208352
一维卷积:
https://www.bilibili.com/video/BV1c44y1Q7fA/?spm_id_from=333.337.search-card.all.click&vd_source=7cf48963f4df908b54a5dae7bb14180e
二维卷积:
https://www.bilibili.com/video/BV18Y411d7tt/?spm_id_from=333.337.search-card.all.click&vd_source=7cf48963f4df908b54a5dae7bb14180e
MobileNet----Depthwise卷积与Pointwise卷积
https://zhuanlan.zhihu.com/p/80041030
BatchNorm
https://www.bilibili.com/video/BV1DM4y1w7J4/?spm_id_from=333.337.search-card.all.click&vd_source=7cf48963f4df908b54a5dae7bb14180e
Pytorch:BatchNorm1d、BatchNorm2d、BatchNorm3d
https://blog.csdn.net/zimiao552147572/article/details/105604193文章来源:https://www.toymoban.com/news/detail-836989.html
B C T/D H W
T/D代表帧数文章来源地址https://www.toymoban.com/news/detail-836989.html
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