[Data loss] Convolutional Block (1x1) with stride > 1 in ResNet50

Course Q&A Deep Learning Specialization Convolutional Neural Networks
1

Hi Coursera community,

I have a question to made clear, that is in ResNet50, some convolutional block is initialized with 1x1 kernel size but stride > 1. As I know 1x1 convolution helps to reduce the number of filters, but stride > 1 will cause some pixels to be lost?

I hope to receive helps from you guys,

Best,

2

It is an excellent point that has been brought up before. Here’s an earlier thread.

It is clearly just ignoring some of the data. It would seem that doing a 2x pooling layer would be a better strategy but it is what it is. The only thing I can suggest is to go read the ResNet papers and see if they comment on this.