多个输入channel的卷积运算

  Since the input and convolution kernel each have $c_i$ channels, we can perform a cross-correlation operation on the two-dimensional tensor of the input and the two-dimensional tensor of the convolution kernel for each channel, adding the $c_i$ results together (summing over the channels) to yield a two-dimensional tensor.

  问题来了，为什么不同channel的结果可以同时相加呢？什么时候进行同时相加呢？

  很神奇的是，卷积层的同一个filter是对不同channel的进行相加运算了。但是池化层（汇聚层）并不进行相加。（不完全准确）。准确的应该是不同filter对不同channel在相同位置进行相加。