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ResNet-18-Caffemodel-on-ImageNet

Accuracy

We reported the test accuracy on ImageNet (ILSVRC2012 Validation Set).

DataSet Top-1 Top-5 Loss
Both256 67.574% 88.1001% 1.33896
Shrt256 69.0801% 89.0321% 1.2711

About shrt 256

Augmented training and test samples:

This improvement was first described by Andrew Howard [Andrew 2014]. Instead of resizing and cropping the image to 256x256, the image is proportionally resized to 256xN(Nx256) with the short edge to 256. Subcrops of 224x224 are then randomly extracted for training.

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ResNet-18 Caffemodel @ilsvrc12 shrt 256 with Top-1 69% Top-5 89%

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