What does it mean by deconvolution (backwards convolution)?
<p>What does it mean by deconvolution or backwards convolution in convolutional neural nets?</p>

<p>I understand convolution, if we consider a 3x3 window W and a kernel k of same size the result of the convolution W*K will be one value. Here k is a matix with 3x3 elements.</p>

<p>In my understanding deconvolution trying to upsample feature maps to get a larger map. Does it use the same convolution matrix which is used to get the feature maps? If not how to calculate the gradients for backpropagation? A detail explanation would be very useful.</p>