Right, exactly. This is manually engineering the lower features, which CNNs just learn. The chief advantage of this technique is a) certain regular wavelets ha

Right, exactly. This is manually engineering the lower features, which CNNs just learn. The chief advantage of this technique is a) certain regular wavelets have performance benefits over convolutions, especially when talking low level/FPGA/ASIC space b) being not learned can be beneficial, as these is nothing to overfit. I can see it being handy for embedded/rasppi like applications. In particular, you can festoon a crude face detector with a dozen Haar filters. End to end training is just soooo convenient though.