文件名称:
Deep Residual Networks
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上传时间: 2019-02-22
详细说明：Deep Residual Networks
Deep Learning Gets Way DeeperIntroduction
Introduction
Deep residual Networks (resEts
Deep Residual Learning for Image Recognition". CVPR 2016 (next week)
A simple and clean framework of training very"deep nets
State-of-the-art performance for
Image classification
Object detection
Semantic segmentation
and more
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recog nition" CVPR 2016
ResNets a ilsvrc coco 2015 competitions
1st places in all five main tracks
ImageNet Classification: " UItra-deep152-layer nets
Image Net Detection: 16% better than 2nd
ImageNet Localization: 27% better than 2nd
COCO Detection: 11%better than 2nd
COCO Segmentation: 12% better than 2nd
improvements are relative numbers
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recog nition" CVPR 2016
Revolution of depth
28.2
25.8
152 layers
16,4
11。7
22 layers 19 layers
67
7.3
3.57
8 layers
8 layers
shallow
LSVRC 15 LSVRC 14 LSVRC 14 LSVRC 13 LSVRC12 LSVRC 11 LSVRC 10
ResNet GoogleNet
VGG
AlexNet
Image Net Classification top-5 error(%
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recog nition" CVPR 2016
Revolution of depth
AlexNet, 8 layers 11x11 conv,96,/4,pool/2
(ILSVRC 2012
5×5c0m256po/2
3x3 conv. 384
3x3 conv, 384
3×3c0mV25600/2
fC,4096
fC,4096
fc.1000
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recog nition" CVPR 2016
Revolution of depth
Lx1l ccnv, 96, /4, pocl/2
AlexNet, 8 layers
VGG, 19 layers
3x3 conv, 64
5X5c0ny256,0
3x3 conv, 64 pool/2
GoogleNet, 22 layers mmm
(ILSVRC 2012
(ILSVRC 2014)
28
(ILSVRC 2014
3×3cnV384
3×3c0n,128,p0o2
3×3cny256,
3×3canv256
fC.4096
3×3canv.256
fc.4096
3x3cnV,256
fc1000
3x3conV,256,p00l/2
3x3 conv, 512
3x3 conv 512
3x3 conv. 512
3x3 conv, 512
3x3 conv,. 512
3x3 conv, 512, pool/2
fc.4096
fc.4096
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image recog nition" CVPR 2016
Revolution of depth
AlexNet, 8 layers
VGG, 19 layers
三
ResNet, 152 layers
(ILSVRC 2012
(ILSVRC 2014)
(ILSVRC 2015)
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recog nition" CVPR 2016
101 layers
Revolution of depth
86
Engines of
visual recognition
66
58
34
16 layers
8 layers
shallow
HOG DPM
AlexNet
VGG
ResNet
(RCNN)
(RCNN)
(Faster RCNN)
PASCAL VOC 2007 Object Detection mAP(%)
*w/ other improvements more data
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recog nition" CVPR 2016
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