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I have read your paper and don't understand why you use the first ten layers of VGG-16 with only three pooling layers instead of all architecture pre-trained model VGG16 ?
Thanks
The text was updated successfully, but these errors were encountered:
ThanhNhann
changed the title
Why do you use all pretrained model VGG16 ?
Why do you don't use all architecture pretrained model VGG16 ?
Nov 21, 2019
I think the reason is that while doing crowd counting, we do not need deep features which contains semantic information. These semantic information might influence the performance since we mainly need shallower feature like edges.
I have read your paper and don't understand why you use the first ten layers of VGG-16 with only three pooling layers instead of all architecture pre-trained model VGG16 ?
Thanks
The text was updated successfully, but these errors were encountered: