【转】学习笔记:GoogLeNet
原作者:lynnandwei 原文地址:http://blog.csdn.net/lynnandwei/article/details/44458033
GoogLeNet, 2014年ILSVRC挑战赛冠军,将Top5 的错误率降低到6.67%. 一个22层的深度网络,论文在http://arxiv.org/pdf/1409.4842v1.pdf,题目为:Going deeper with convolutions。(每次看这么简洁优雅的题目,就想吐槽国内写paper的 八股文题目)。GoogLeNet这个名字也是挺有意思的,为了像开山鼻祖的LeNet网络致敬,他们选择了这样的名字。
BVLC在caffe中给出了网络的实现:https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet
模型下载地址:http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel
从论文里整理了一张这个22个层次的模型的图出来(如果考虑pooling层是27层),先将模型跑了一遍结果,还是那只猫:
直观输出是如下,觉得挺准确:
[287 281 285 282 283]
['n02127052 lynx, catamount' 'n02123045 tabby, tabby cat'
'n02124075 Egyptian cat' 'n02123159 tiger cat' 'n02123394 Persian cat']
caffe的实现和原来论文的模型是有不同的:
not training with the relighting data-augmentation;
not training with the scale or aspect-ratio data-augmentation;
uses "xavier" to initialize the weights instead of "gaussian";
quick_solver.prototxt uses a different learning rate decay policy than the original solver.prototxt, that allows a much faster training (60 epochs vs 250 epochs);
The bundled model is the iteration 2,400,000 snapshot (60 epochs) using quick_solver.prototxt
但是准确度还是达到了 a top-1 accuracy 68.7% (31.3% error) and a top-5 accuracy 88.9% (11.1% error)
我们来分析一下这个模型的层次关系:
原始数据,输入为224*224*3
第一层卷积层 conv1 ,pad是3,64个特征,7*7 步长为2,输出特征为 112*112*64,然后进行relu,经过pool1(红色的max pool) 进行pooling 3*3的核,步长为2, [(112 - 3+1)/2]+1 = 56 特征为56*56*64 , 然后进行norm
第二层卷积层 conv2, pad是1,3*3,192个特征,输出为56*56*192,然后进行relu,进行norm,经过pool2进行pooling,3*3的核,步长为2 输出为28*28*192 然后进行split 分成四个支线
- Setting up pool2/3x3_s2
- I0319 23:50:37.405478 5765 net.cpp:103] Top shape: 10 192 28 28 (1505280)
- I0319 23:50:37.405484 5765 net.cpp:113] Memory required for data: 174612480
- I0319 23:50:37.405495 5765 net.cpp:67] Creating Layer pool2/3x3_s2_pool2/3x3_s2_0_split
- I0319 23:50:37.405503 5765 net.cpp:394] pool2/3x3_s2_pool2/3x3_s2_0_split <- pool2/3x3_s2
- I0319 23:50:37.405515 5765 net.cpp:356] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_0
- I0319 23:50:37.405531 5765 net.cpp:356] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_1
- I0319 23:50:37.405545 5765 net.cpp:356] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_2
- I0319 23:50:37.405557 5765 net.cpp:356] pool2/3x3_s2_pool2/3x3_s2_0_split -> pool2/3x3_s2_pool2/3x3_s2_0_split_3
- I0319 23:50:37.405567 5765 net.cpp:96] Setting up pool2/3x3_s2_pool2/3x3_s2_0_split
- I0319 23:50:37.405577 5765 net.cpp:103] Top shape: 10 192 28 28 (1505280)
- I0319 23:50:37.405582 5765 net.cpp:103] Top shape: 10 192 28 28 (1505280)
- I0319 23:50:37.405587 5765 net.cpp:103] Top shape: 10 192 28 28 (1505280)
- I0319 23:50:37.405592 5765 net.cpp:103] Top shape: 10 192 28 28 (1505280)
- I0319 23:50:37.405597 5765 net.cpp:113] Memory required for data: 198696960
- I0319 23:50:37.405611 5765 net.cpp:67] Creating Layer inception_3a/1x1^M
第三层开始时 inception module ,这个的思想受到使用不同尺度的Gabor过滤器来处理多尺度问题,inception module采用不同尺度的卷积核来处理问题。3a 包含 四个支线:
1: 64个1*1的卷积核(之后进行RULE计算) 变成28*28*64
2: 96个1*1的卷积核 作为3*3卷积核之前的reduce,变成28*28*96, 进行relu计算后,再进行128个3*3的卷积,pad为1, 28*28*128
3:16个1*1的卷积核 作为5*5卷积核之前的reduce,变成28*28*16, 进行relu计算后,再进行32个5*5的卷积,pad为2,变成28*28*32
4:pool层,3*3的核,pad为1,输出还是28*28*192,然后进行32个1*1的卷积,变成28*28*32。
将四个结果进行连接,输出为28*28*256
然后将3a的结果又分成四条支线,开始建立3b的inception module
3b
1:128个1*1的卷积核(之后进行RULE计算) 变成28*28*128
2:128个1*1的卷积核 作为3*3卷积核之前的reduce,变成28*28*128, 再进行192个3*3的卷积,pad为1, 28*28*192,进行relu计算
3:32个1*1的卷积核 作为5*5卷积核之前的reduce,变成28*28*32, 进行relu计算后,再进行96个5*5的卷积,pad为2,变成28*28*96
4:pool层,3*3的核,pad为1,输出还是28*28*256,然后进行64个1*1的卷积,变成28*28*64。
将四个结果进行连接,输出为28*28*480
同理依次推算,数据变化如下表:
一部分输出结果如下:
I0319 22:27:51.257917 5080 net.cpp:208] This network produces output prob
- I0319 22:27:51.258116 5080 net.cpp:467] Collecting Learning Rate and Weight Decay.
- I0319 22:27:51.258162 5080 net.cpp:219] Network initialization done.
- I0319 22:27:51.258167 5080 net.cpp:220] Memory required for data: 545512320
- I0319 22:27:51.345417 5080 net.cpp:702] Ignoring source layer data
- I0319 22:27:51.345443 5080 net.cpp:702] Ignoring source layer label_data_1_split
- I0319 22:27:51.345448 5080 net.cpp:705] Copying source layer conv1/7x7_s2
- I0319 22:27:51.345542 5080 net.cpp:705] Copying source layer conv1/relu_7x7
- I0319 22:27:51.345548 5080 net.cpp:705] Copying source layer pool1/3x3_s2
- I0319 22:27:51.345553 5080 net.cpp:705] Copying source layer pool1/norm1
- I0319 22:27:51.345558 5080 net.cpp:705] Copying source layer conv2/3x3_reduce
- I0319 22:27:51.345600 5080 net.cpp:705] Copying source layer conv2/relu_3x3_reduce
- I0319 22:27:51.345607 5080 net.cpp:705] Copying source layer conv2/3x3
- I0319 22:27:51.346571 5080 net.cpp:705] Copying source layer conv2/relu_3x3
- I0319 22:27:51.346580 5080 net.cpp:705] Copying source layer conv2/norm2
- I0319 22:27:51.346585 5080 net.cpp:705] Copying source layer pool2/3x3_s2
- I0319 22:27:51.346590 5080 net.cpp:705] Copying source layer pool2/3x3_s2_pool2/3x3_s2_0_split
- I0319 22:27:51.346595 5080 net.cpp:705] Copying source layer inception_3a/1x1
- I0319 22:27:51.346706 5080 net.cpp:705] Copying source layer inception_3a/relu_1x1
- I0319 22:27:51.346712 5080 net.cpp:705] Copying source layer inception_3a/3x3_reduce
- I0319 22:27:51.346879 5080 net.cpp:705] Copying source layer inception_3a/relu_3x3_reduce
- I0319 22:27:51.346885 5080 net.cpp:705] Copying source layer inception_3a/3x3
- I0319 22:27:51.347844 5080 net.cpp:705] Copying source layer inception_3a/relu_3x3
- I0319 22:27:51.347851 5080 net.cpp:705] Copying source layer inception_3a/5x5_reduce
- I0319 22:27:51.347885 5080 net.cpp:705] Copying source layer inception_3a/relu_5x5_reduce
- I0319 22:27:51.347892 5080 net.cpp:705] Copying source layer inception_3a/5x5
- I0319 22:27:51.348008 5080 net.cpp:705] Copying source layer inception_3a/relu_5x5
- I0319 22:27:51.348014 5080 net.cpp:705] Copying source layer inception_3a/pool
- I0319 22:27:51.348019 5080 net.cpp:705] Copying source layer inception_3a/pool_proj
- I0319 22:27:51.348080 5080 net.cpp:705] Copying source layer inception_3a/relu_pool_proj
- I0319 22:27:51.348085 5080 net.cpp:705] Copying source layer inception_3a/output
- I0319 22:27:51.348091 5080 net.cpp:705] Copying source layer inception_3a/output_inception_3a/output_0_split
- I0319 22:27:51.348096 5080 net.cpp:705] Copying source layer inception_3b/1x1
- I0319 22:27:51.348398 5080 net.cpp:705] Copying source layer inception_3b/relu_1x1
- I0319 22:27:51.348405 5080 net.cpp:705] Copying source layer inception_3b/3x3_reduce
- I0319 22:27:51.348700 5080 net.cpp:705] Copying source layer inception_3b/relu_3x3_reduce
- I0319 22:27:51.348707 5080 net.cpp:705] Copying source layer inception_3b/3x3
- I0319 22:27:51.350611 5080 net.cpp:705] Copying source layer inception_3b/relu_3x3
- I0319 22:27:51.350620 5080 net.cpp:705] Copying source layer inception_3b/5x5_reduce
- I0319 22:27:51.350699 5080 net.cpp:705] Copying source layer inception_3b/relu_5x5_reduce
- I0319 22:27:51.350705 5080 net.cpp:705] Copying source layer inception_3b/5x5
- I0319 22:27:51.351372 5080 net.cpp:705] Copying source layer inception_3b/relu_5x5
- I0319 22:27:51.351378 5080 net.cpp:705] Copying source layer inception_3b/pool
- I0319 22:27:51.351384 5080 net.cpp:705] Copying source layer inception_3b/pool_proj
- I0319 22:27:51.351546 5080 net.cpp:705] Copying source layer inception_3b/relu_pool_proj
- I0319 22:27:51.351552 5080 net.cpp:705] Copying source layer inception_3b/output
- I0319 22:27:51.351558 5080 net.cpp:705] Copying source layer pool3/3x3_s2
- I0319 22:27:51.351563 5080 net.cpp:705] Copying source layer pool3/3x3_s2_pool3/3x3_s2_0_split
- I0319 22:27:51.351569 5080 net.cpp:705] Copying source layer inception_4a/1x1
- I0319 22:27:51.352367 5080 net.cpp:705] Copying source layer inception_4a/relu_1x1
- I0319 22:27:51.352375 5080 net.cpp:705] Copying source layer inception_4a/3x3_reduce
- I0319 22:27:51.352782 5080 net.cpp:705] Copying source layer inception_4a/relu_3x3_reduce
- I0319 22:27:51.352789 5080 net.cpp:705] Copying source layer inception_4a/3x3
- I0319 22:27:51.354333 5080 net.cpp:705] Copying source layer inception_4a/relu_3x3
- I0319 22:27:51.354341 5080 net.cpp:705] Copying source layer inception_4a/5x5_reduce
- I0319 22:27:51.354420 5080 net.cpp:705] Copying source layer inception_4a/relu_5x5_reduce
- I0319 22:27:51.354429 5080 net.cpp:705] Copying source layer inception_4a/5x5
- I0319 22:27:51.354601 5080 net.cpp:705] Copying source layer inception_4a/relu_5x5
- I0319 22:27:51.354609 5080 net.cpp:705] Copying source layer inception_4a/pool
- I0319 22:27:51.354614 5080 net.cpp:705] Copying source layer inception_4a/pool_proj
- I0319 22:27:51.354887 5080 net.cpp:705] Copying source layer inception_4a/relu_pool_proj
- I0319 22:27:51.354894 5080 net.cpp:705] Copying source layer inception_4a/output
- I0319 22:27:51.354900 5080 net.cpp:705] Copying source layer inception_4a/output_inception_4a/output_0_split
- I0319 22:27:51.354910 5080 net.cpp:702] Ignoring source layer loss1/ave_pool
- I0319 22:27:51.354918 5080 net.cpp:702] Ignoring source layer loss1/conv
- I0319 22:27:51.354923 5080 net.cpp:702] Ignoring source layer loss1/relu_conv
- I0319 22:27:51.354930 5080 net.cpp:702] Ignoring source layer loss1/fc
- I0319 22:27:51.354936 5080 net.cpp:702] Ignoring source layer loss1/relu_fc
- I0319 22:27:51.354943 5080 net.cpp:702] Ignoring source layer loss1/drop_fc
- I0319 22:27:51.354950 5080 net.cpp:702] Ignoring source layer loss1/classifier
- I0319 22:27:51.354956 5080 net.cpp:702] Ignoring source layer loss1/loss
- I0319 22:27:51.354962 5080 net.cpp:705] Copying source layer inception_4b/1x1
- I0319 22:27:51.355681 5080 net.cpp:705] Copying source layer inception_4b/relu_1x1
- I0319 22:27:51.355690 5080 net.cpp:705] Copying source layer inception_4b/3x3_reduce
- I0319 22:27:51.356190 5080 net.cpp:705] Copying source layer inception_4b/relu_3x3_reduce
- I0319 22:27:51.356199 5080 net.cpp:705] Copying source layer inception_4b/3x3
- I0319 22:27:51.358134 5080 net.cpp:705] Copying source layer inception_4b/relu_3x3
- I0319 22:27:51.358144 5080 net.cpp:705] Copying source layer inception_4b/5x5_reduce
- I0319 22:27:51.358256 5080 net.cpp:705] Copying source layer inception_4b/relu_5x5_reduce
- I0319 22:27:51.358263 5080 net.cpp:705] Copying source layer inception_4b/5x5
- I0319 22:27:51.358608 5080 net.cpp:705] Copying source layer inception_4b/relu_5x5
- I0319 22:27:51.358616 5080 net.cpp:705] Copying source layer inception_4b/pool
- I0319 22:27:51.358623 5080 net.cpp:705] Copying source layer inception_4b/pool_proj
- I0319 22:27:51.358917 5080 net.cpp:705] Copying source layer inception_4b/relu_pool_proj
- I0319 22:27:51.358925 5080 net.cpp:705] Copying source layer inception_4b/output
- I0319 22:27:51.358932 5080 net.cpp:705] Copying source layer inception_4b/output_inception_4b/output_0_split
- I0319 22:27:51.358937 5080 net.cpp:705] Copying source layer inception_4c/1x1
- I0319 22:27:51.359519 5080 net.cpp:705] Copying source layer inception_4c/relu_1x1
- I0319 22:27:51.359526 5080 net.cpp:705] Copying source layer inception_4c/3x3_reduce
- I0319 22:27:51.360097 5080 net.cpp:705] Copying source layer inception_4c/relu_3x3_reduce
- I0319 22:27:51.360105 5080 net.cpp:705] Copying source layer inception_4c/3x3
- I0319 22:27:51.362634 5080 net.cpp:705] Copying source layer inception_4c/relu_3x3
- I0319 22:27:51.362643 5080 net.cpp:705] Copying source layer inception_4c/5x5_reduce
- I0319 22:27:51.362757 5080 net.cpp:705] Copying source layer inception_4c/relu_5x5_reduce
- I0319 22:27:51.362764 5080 net.cpp:705] Copying source layer inception_4c/5x5
- I0319 22:27:51.363106 5080 net.cpp:705] Copying source layer inception_4c/relu_5x5
- I0319 22:27:51.363114 5080 net.cpp:705] Copying source layer inception_4c/pool
- I0319 22:27:51.363121 5080 net.cpp:705] Copying source layer inception_4c/pool_proj
- I0319 22:27:51.363415 5080 net.cpp:705] Copying source layer inception_4c/relu_pool_proj
- I0319 22:27:51.363423 5080 net.cpp:705] Copying source layer inception_4c/output
- I0319 22:27:51.363430 5080 net.cpp:705] Copying source layer inception_4c/output_inception_4c/output_0_split
- I0319 22:27:51.363436 5080 net.cpp:705] Copying source layer inception_4d/1x1
- I0319 22:27:51.363937 5080 net.cpp:705] Copying source layer inception_4d/relu_1x1
- I0319 22:27:51.363945 5080 net.cpp:705] Copying source layer inception_4d/3x3_reduce
- I0319 22:27:51.364591 5080 net.cpp:705] Copying source layer inception_4d/relu_3x3_reduce
- I0319 22:27:51.364600 5080 net.cpp:705] Copying source layer inception_4d/3x3
- I0319 22:27:51.367797 5080 net.cpp:705] Copying source layer inception_4d/relu_3x3
- I0319 22:27:51.367806 5080 net.cpp:705] Copying source layer inception_4d/5x5_reduce
- I0319 22:27:51.367959 5080 net.cpp:705] Copying source layer inception_4d/relu_5x5_reduce
- I0319 22:27:51.367966 5080 net.cpp:705] Copying source layer inception_4d/5x5
- I0319 22:27:51.368420 5080 net.cpp:705] Copying source layer inception_4d/relu_5x5
- I0319 22:27:51.368428 5080 net.cpp:705] Copying source layer inception_4d/pool
- I0319 22:27:51.368435 5080 net.cpp:705] Copying source layer inception_4d/pool_proj
- I0319 22:27:51.368726 5080 net.cpp:705] Copying source layer inception_4d/relu_pool_proj
- I0319 22:27:51.368733 5080 net.cpp:705] Copying source layer inception_4d/output
- I0319 22:27:51.368739 5080 net.cpp:705] Copying source layer inception_4d/output_inception_4d/output_0_split
- I0319 22:27:51.368748 5080 net.cpp:702] Ignoring source layer loss2/ave_pool
- I0319 22:27:51.368755 5080 net.cpp:702] Ignoring source layer loss2/conv
- I0319 22:27:51.368762 5080 net.cpp:702] Ignoring source layer loss2/relu_conv
- I0319 22:27:51.368768 5080 net.cpp:702] Ignoring source layer loss2/fc
- I0319 22:27:51.368774 5080 net.cpp:702] Ignoring source layer loss2/relu_fc
- I0319 22:27:51.368780 5080 net.cpp:702] Ignoring source layer loss2/drop_fc
- I0319 22:27:51.368788 5080 net.cpp:702] Ignoring source layer loss2/classifier
- I0319 22:27:51.368794 5080 net.cpp:702] Ignoring source layer loss2/loss
- I0319 22:27:51.368800 5080 net.cpp:705] Copying source layer inception_4e/1x1
- I0319 22:27:51.369971 5080 net.cpp:705] Copying source layer inception_4e/relu_1x1
- I0319 22:27:51.369981 5080 net.cpp:705] Copying source layer inception_4e/3x3_reduce
- I0319 22:27:51.370717 5080 net.cpp:705] Copying source layer inception_4e/relu_3x3_reduce
- I0319 22:27:51.370725 5080 net.cpp:705] Copying source layer inception_4e/3x3
- I0319 22:27:51.374668 5080 net.cpp:705] Copying source layer inception_4e/relu_3x3
- I0319 22:27:51.374678 5080 net.cpp:705] Copying source layer inception_4e/5x5_reduce
- I0319 22:27:51.374831 5080 net.cpp:705] Copying source layer inception_4e/relu_5x5_reduce
- I0319 22:27:51.374840 5080 net.cpp:705] Copying source layer inception_4e/5x5
- I0319 22:27:51.375728 5080 net.cpp:705] Copying source layer inception_4e/relu_5x5
- I0319 22:27:51.375737 5080 net.cpp:705] Copying source layer inception_4e/pool
- I0319 22:27:51.375744 5080 net.cpp:705] Copying source layer inception_4e/pool_proj
- I0319 22:27:51.376332 5080 net.cpp:705] Copying source layer inception_4e/relu_pool_proj
- I0319 22:27:51.376340 5080 net.cpp:705] Copying source layer inception_4e/output
- I0319 22:27:51.376346 5080 net.cpp:705] Copying source layer pool4/3x3_s2
- I0319 22:27:51.376353 5080 net.cpp:705] Copying source layer pool4/3x3_s2_pool4/3x3_s2_0_split
- I0319 22:27:51.376359 5080 net.cpp:705] Copying source layer inception_5a/1x1
- I0319 22:27:51.378186 5080 net.cpp:705] Copying source layer inception_5a/relu_1x1
- I0319 22:27:51.378196 5080 net.cpp:705] Copying source layer inception_5a/3x3_reduce
- I0319 22:27:51.379343 5080 net.cpp:705] Copying source layer inception_5a/relu_3x3_reduce
- I0319 22:27:51.379353 5080 net.cpp:705] Copying source layer inception_5a/3x3
- I0319 22:27:51.383293 5080 net.cpp:705] Copying source layer inception_5a/relu_3x3
- I0319 22:27:51.383303 5080 net.cpp:705] Copying source layer inception_5a/5x5_reduce
- I0319 22:27:51.383548 5080 net.cpp:705] Copying source layer inception_5a/relu_5x5_reduce
- I0319 22:27:51.383558 5080 net.cpp:705] Copying source layer inception_5a/5x5
- I0319 22:27:51.384449 5080 net.cpp:705] Copying source layer inception_5a/relu_5x5
- I0319 22:27:51.384459 5080 net.cpp:705] Copying source layer inception_5a/pool
- I0319 22:27:51.384465 5080 net.cpp:705] Copying source layer inception_5a/pool_proj
- I0319 22:27:51.385397 5080 net.cpp:705] Copying source layer inception_5a/relu_pool_proj
- I0319 22:27:51.385406 5080 net.cpp:705] Copying source layer inception_5a/output
- I0319 22:27:51.385414 5080 net.cpp:705] Copying source layer inception_5a/output_inception_5a/output_0_split
- I0319 22:27:51.385421 5080 net.cpp:705] Copying source layer inception_5b/1x1
- I0319 22:27:51.388157 5080 net.cpp:705] Copying source layer inception_5b/relu_1x1
- I0319 22:27:51.388166 5080 net.cpp:705] Copying source layer inception_5b/3x3_reduce
- I0319 22:27:51.389539 5080 net.cpp:705] Copying source layer inception_5b/relu_3x3_reduce
- I0319 22:27:51.389549 5080 net.cpp:705] Copying source layer inception_5b/3x3
- I0319 22:27:51.395212 5080 net.cpp:705] Copying source layer inception_5b/relu_3x3
- I0319 22:27:51.395225 5080 net.cpp:705] Copying source layer inception_5b/5x5_reduce
- I0319 22:27:51.395584 5080 net.cpp:705] Copying source layer inception_5b/relu_5x5_reduce
- I0319 22:27:51.395594 5080 net.cpp:705] Copying source layer inception_5b/5x5
- I0319 22:27:51.396921 5080 net.cpp:705] Copying source layer inception_5b/relu_5x5
- I0319 22:27:51.396931 5080 net.cpp:705] Copying source layer inception_5b/pool
- I0319 22:27:51.396939 5080 net.cpp:705] Copying source layer inception_5b/pool_proj
- I0319 22:27:51.397862 5080 net.cpp:705] Copying source layer inception_5b/relu_pool_proj
- I0319 22:27:51.397871 5080 net.cpp:705] Copying source layer inception_5b/output
- I0319 22:27:51.397879 5080 net.cpp:705] Copying source layer pool5/7x7_s1
- I0319 22:27:51.397886 5080 net.cpp:705] Copying source layer pool5/drop_7x7_s1
- I0319 22:27:51.397893 5080 net.cpp:705] Copying source layer loss3/classifier
- I0319 22:27:51.406652 5080 net.cpp:702] Ignoring source layer loss3/loss3
材料集合:
http://deeplearning.net/2014/09/19/googles-entry-to-imagenet-2014-challenge/
[1] Imagenet 2014 LSVRC results, http://karpathy.github.io/2014/09/02/what-i-learned-from-competing-against-a-convnet-on-imagenet/,Last retrieved on: 19-09-2014.
[2] Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich, Going Deeper with Convolutions, Arxiv Link: http://arxiv.org/abs/1409.4842.
[3] GoogLeNet presentation, http://image-net.org/challenges/LSVRC/2014/slides/GoogLeNet.pptx, Last retrieved on: 19-09.2014..
[4] What I learned from competing against a convnet on imagenet, http://karpathy.github.io/2014/09/02/what-i-learned-from-competing-against-a-convnet-on-imagenet/, Last retrieved on: 19-09-2014.
[5] Girshick, Ross, et al. “Rich feature hierarchies for accurate object detection and semantic segmentation.” arXiv preprint arXiv:1311.2524 (2013).
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