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文件名称:SceneTextCNN_demo.tar

  • 所属分类：
    AI-NN-PR
  • 标签属性：
    [Matlab] [源码]
  • 上传时间：
    2013-03-16
  • 文件大小：
    58.22mb
  • 已下载：
    3次
  • 提 供 者：
    tw***
  • 相关连接：
    无
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修正介绍说明

介绍说明－－下载内容来自于网络，使用问题请自行百度

端至端卷积神经网络的文字识别,代码演示包.

它包含我们的论文中使用的所有主要组成部分: kmeans无监督特征学习 + 卷积神经网络(CNN)-This is a demo package of the code we used for our paper, "End-to-End

Text Recognition with Convolutional Neural Networks", T. Wang, D. Wu,

A. Coates, A. Ng, in ICPR 2012.



The package is provided to facilitate understanding of the algorithms

used in our paper. It contains demos to all the major components of our

end-to-end system. Because of speed considerations, the CNN

architectures as well as dataset sizes provided in this package are

much smaller than the actural ones used in the paper, although the

algorithms themselves are identical. We also provide our trained models

together with code to reproduce major results reported in our paper.
(系统自动生成,下载前可以参看下载内容)

下载文件列表

SceneTextCNN_demo/
SceneTextCNN_demo/models/
SceneTextCNN_demo/icdarTestLex/
SceneTextCNN_demo/finetune/
SceneTextCNN_demo/kmeans/
SceneTextCNN_demo/extract1stLayerFeatures/
SceneTextCNN_demo/trainDetector/
SceneTextCNN_demo/trainClassifier/
SceneTextCNN_demo/detectorDemo/
SceneTextCNN_demo/structs/
SceneTextCNN_demo/icdarTestLex/lex5/
SceneTextCNN_demo/icdarTestLex/lex20/
SceneTextCNN_demo/icdarTestLex/lex50/
SceneTextCNN_demo/finetune/models/
SceneTextCNN_demo/finetune/convCode/
SceneTextCNN_demo/finetune/poolFunc/
SceneTextCNN_demo/finetune/stackCode/
SceneTextCNN_demo/finetune/minFunc/
SceneTextCNN_demo/detectorDemo/models/
SceneTextCNN_demo/finetune/minFunc/logistic/
SceneTextCNN_demo/loadRecognitionModel.m
SceneTextCNN_demo/getRecogScores_convnet.m
SceneTextCNN_demo/beam_search_step.m
SceneTextCNN_demo/ascii2label.m
SceneTextCNN_demo/e2e_demo.m
SceneTextCNN_demo/license.txt
SceneTextCNN_demo/score2Word.m
SceneTextCNN_demo/score2WordBounds.m
SceneTextCNN_demo/parseXML.m
SceneTextCNN_demo/README
SceneTextCNN_demo/wtnms.m
SceneTextCNN_demo/filterScores.m
SceneTextCNN_demo/wordRecog.m
SceneTextCNN_demo/getIcdarTrainStruct.m
SceneTextCNN_demo/getIcdarTestStruct.m
SceneTextCNN_demo/getMatchScore.m
SceneTextCNN_demo/getSVTStruct.m
SceneTextCNN_demo/e2e_visualize.m
SceneTextCNN_demo/getFScore.m
SceneTextCNN_demo/models/best_classifier_convnet.mat
SceneTextCNN_demo/models/detector_cnn.mat
SceneTextCNN_demo/models/best_classifier_sig_mu.mat
SceneTextCNN_demo/models/best_centroids.mat
SceneTextCNN_demo/finetune/triangleRect.m
SceneTextCNN_demo/finetune/create_detector_data.m
SceneTextCNN_demo/finetune/bsxfunwrap.m
SceneTextCNN_demo/finetune/create_icdar_data.m
SceneTextCNN_demo/finetune/triangleRectGrad.m
SceneTextCNN_demo/finetune/tanhInitRand.m
SceneTextCNN_demo/finetune/l2svmLoss.m
SceneTextCNN_demo/finetune/convnet_wrapper_svm_fix1stlayer.m
SceneTextCNN_demo/finetune/svmConvLoss.m
SceneTextCNN_demo/finetune/svmConvPredict.m
SceneTextCNN_demo/finetune/svmConvSetup.m
SceneTextCNN_demo/kmeans/first_layer_centroids_detector_48.mat
SceneTextCNN_demo/kmeans/first_layer_centroids.mat
SceneTextCNN_demo/kmeans/display_network.m
SceneTextCNN_demo/kmeans/kmeansDemo.m
SceneTextCNN_demo/kmeans/selectCentroids.m
SceneTextCNN_demo/kmeans/normalizeAndZCA.m
SceneTextCNN_demo/kmeans/run_projection_kmeans.m
SceneTextCNN_demo/kmeans/filters1.jpg
SceneTextCNN_demo/extract1stLayerFeatures/prepData.m
SceneTextCNN_demo/extract1stLayerFeatures/triangleRect.m
SceneTextCNN_demo/extract1stLayerFeatures/extractFeatures.m
SceneTextCNN_demo/extract1stLayerFeatures/createFeatures.m
SceneTextCNN_demo/trainDetector/train_detector.m
SceneTextCNN_demo/trainClassifier/train_classifier.m
SceneTextCNN_demo/detectorDemo/loadDataPreprocess.m
SceneTextCNN_demo/detectorDemo/getImgNames.m
SceneTextCNN_demo/detectorDemo/firstLayerFeatures.m
SceneTextCNN_demo/detectorDemo/firstLayerFeaturesHelper.m
SceneTextCNN_demo/detectorDemo/trainDetectorCNN.m
SceneTextCNN_demo/detectorDemo/cstackToFilterStack.m
SceneTextCNN_demo/detectorDemo/runDetectorDemo.m
SceneTextCNN_demo/detectorDemo/visualizeBoxes.m
SceneTextCNN_demo/detectorDemo/runDetectorFull.m
SceneTextCNN_demo/detectorDemo/nmsLineResponse.m
SceneTextCNN_demo/detectorDemo/nmsBBoxes.m
SceneTextCNN_demo/detectorDemo/findLinesFull.m
SceneTextCNN_demo/detectorDemo/findBoxesFull.m
SceneTextCNN_demo/detectorDemo/fullImageForwardPropHelper.m
SceneTextCNN_demo/detectorDemo/fullImageForwardProp.m
SceneTextCNN_demo/detectorDemo/README
SceneTextCNN_demo/detectorDemo/computeResponses.m
SceneTextCNN_demo/structs/svtWordTestStruct.mat
SceneTextCNN_demo/icdarTestLex/lex5/I00127.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00126.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00125.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00124.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00123.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00122.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00121.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00120.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00119.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00118.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00117.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00116.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00115.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00114.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00113.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00112.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00111.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00110.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00109.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00108.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00107.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00106.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00105.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00104.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00103.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00102.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00101.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00100.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00099.jpg.txt
SceneTextCNN_demo/icdarTestLex/lex5/I00098.jpg.txt

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