资源算法ResNet-18-Caffemodel-on-ImageNet

ResNet-18-Caffemodel-on-ImageNet

2020-02-21 | |  30 |   0 |   0

ResNet-18-Caffemodel-on-ImageNet

Accuracy

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

DataSetTop-1Top-5Loss
Both25667.574%88.1001%1.33896
Shrt25669.0801%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.

Model Link

OneDrive
BaiduCloud


上一篇:st-resnet

下一篇:pytorch-resnet3d

用户评价
全部评价

热门资源

  • Keras-ResNeXt

    Keras ResNeXt Implementation of ResNeXt models...

  • seetafaceJNI

    项目介绍 基于中科院seetaface2进行封装的JAVA...

  • spark-corenlp

    This package wraps Stanford CoreNLP annotators ...

  • capsnet-with-caps...

    CapsNet with capsule-wise convolution Project ...

  • inferno-boilerplate

    This is a very basic boilerplate example for pe...