内容简介:以爱与青春为名,陪你一路成长
点下方“ 深度学习与先进智能 决策 ”进 号内搜
以爱与青春为名,陪你一路成长
大多数时候,人们使用不同的深度学习框架和标准开发 工具 箱。(SDKs),用于实施深度学习方法,具体如下:
框架
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Tensorflow: https://www.tensorflow.org/
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Caffe: http://caffe.berkeleyvision.org/
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KERAS: https://keras.io/
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Theano: http://deeplearning.net/software/theano/
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Torch: http://torch.ch/
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PyTorch: http://pytorch.org/
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Lasagne: https://lasagne.readthedocs.io/en/latest/
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DL4J (DeepLearning4J): https://deeplearning4j.org/
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Chainer: http://chainer.org/
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DIGITS: https://developer.nvidia.com/digits
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CNTK (Microsoft):https://github.com/Microsoft/CNTK
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MatConvNet: http://www.vlfeat.org/matconvnet/
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MINERVA: https://github.com/dmlc/minerva
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MXNET: https://github.com/dmlc/mxnet
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OpenDeep: http://www.opendeep.org/
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PuRine: https://github.com/purine/purine2
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PyLerarn2: http://deeplearning.net/software/pylearn2/
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TensorLayer: https://github.com/zsdonghao/tensorlayer
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LBANN: https://github.com/LLNL/lbann
SDKs
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cuDNN: https://developer.nvidia.com/cudnn
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TensorRT: https://developer.nvidia.com/tensorrt
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DeepStreamSDK: https://developer.nvidia.com/deepstream-sdk
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cuBLAS: https://developer.nvidia.com/cublas
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cuSPARSE: http://docs.nvidia.com/cuda/cusparse/
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NCCL: https://devblogs.nvidia.com/parallelforall/fast-multi-gpu-collectives-nccl/
基准数据集
以下是常用于评估不同应用领域的深度学习方法的基准数据集列表。
图像分类或检测或分割
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MNIST: http://yann.lecun.com/exdb/mnist/
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CIFAR 10/100: https://www.cs.toronto.edu/~kriz/cifar.html
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SVHN/ SVHN2: http://ufldl.stanford.edu/housenumbers/
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CalTech 101/256: http://www.vision.caltech.edu/Image_Datasets/Caltech101/
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STL-10: https://cs.stanford.edu/~acoates/stl10/
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NORB: http://www.cs.nyu.edu/~ylclab/data/norb-v1.0/
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SUN-dataset: http://groups.csail.mit.edu/vision/SUN/
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ImageNet: http://www.image-net.org/
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National Data Science Bowl Competition: http://www.datasciencebowl.com/
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COIL 20/100: http://www.cs.columbia.edu/CAVE/software/softlib/coil-20.php
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MS COCO DATASET: http://mscoco.org/
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MIT-67 scene dataset: http://web.mit.edu/torralba/www/indoor.html
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Caltech-UCSD Birds-200 dataset: http://www.vision.caltech.edu/visipedia/CUB-200- 2011.html
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Pascal VOC 2007 dataset: http://host.robots.ox.ac.uk/pascal/VOC/voc2007/
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H3D Human Attributes dataset: https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/shape/poselets/
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Face recognition dataset: http://vis-www.cs.umass.edu/lfw/
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For more data-set visit: https://www.kaggle.com/
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http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm
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Recently Introduced Datasets in Sept. 2016:
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Google Open Images (~9M images)—https://github.com/openimages/dataset
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Youtube-8M (8M videos: https://research.google.com/youtube8m/
文本分类
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Reuters-21578 Text Categorization Collection: http://kdd.ics.uci.edu/databases/reuters21578/reuters21578.html
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Sentiment analysis from Stanford: http://ai.stanford.edu/~amaas/data/sentiment/
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Movie sentiment analysis from Cornel: http://www.cs.cornell.edu/people/pabo/movie-review-data/ Free eBooks : https://www.gutenberg.org/
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Brown and stanford corpus on present americal english: https://en.wikipedia.org/wiki/Brown_Corpus
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Google 1Billion word corpus: https://github.com/ciprian-chelba/1-billion-wordlanguage- modeling-benchmark
图像编码
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Flickr-8k: http://nlp.cs.illinois.edu/HockenmaierGroup/8k-pictures.html
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Common Objects in Context (COCO):http://cocodataset.org/#overview;http://sidgan.me/technical/2016/01/09/Exploring-Datasets
机器翻译
- Pairs of sentences in English and French : https://www.isi.edu/naturallanguage/ download/hansard/
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European Parliament Proceedings parallel Corpus 196-2011: http://www.statmt.org/europarl/
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The statistics for machine translation: http://www.statmt.org/
问答
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Stanford Question Answering Dataset (SQuAD): https://rajpurkar.github.io/SQuADexplorer/
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Dataset from DeepMind: https://github.com/deepmind/rc-data
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Amazon dataset:http://jmcauley.ucsd.edu/data/amazon/qa/,;http://trec.nist.gov/data/qamain...,;http://www.ark.cs.cmu.edu/QA-data/,;http://webscope.sandbox.yahoo.co...,;http://blog.stackoverflow.com/20..
语音辨识
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TIMIT: https://catalog.ldc.upenn.edu/LDC93S1
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Voxforge: http://voxforge.org/
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Open Speech and Language Resources: http://www.openslr.org/12/
文章摘要
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https://archive.ics.uci.edu/ml/datasets/Legal+Case+Reports
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http://www-nlpir.nist.gov/related_projects/tipster_summac/cmp_lg.html
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https://catalog.ldc.upenn.edu/LDC2002T31
情感分析
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IMDB dataset: http://www.imdb.com/
高光谱图像分析
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http://www.ehu.eus/ccwintco/index.php/Hyperspectral_Remote_Sensing_Scenes
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https://engineering.purdue.edu/~biehl/MultiSpec/hyperspectral.html
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http://www2.isprs.org/commissions/comm3/wg4/HyRANK.html
期刊和会议
Conferences
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Neural Information Processing System (NIPS)
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International Conference on Learning Representation (ICLR): What are you doing for Deep Learning?
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International Conference on Machine Learning (ICML)
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Computer Vision and Pattern Recognition (CVPR): What are you doing with Deep Learning?
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International Conference on Computer Vision (ICCV)
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European Conference on Computer Vision (ECCV)
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British Machine Vision Conference (BMVC)
Journal
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Journal of Machine Learning Research (JMLR)
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IEEE Transaction of Neural Network and Learning System (
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IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
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Computer Vision and Image Understanding (CVIU)
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Pattern Recognition Letter
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Neural Computing and Application
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International Journal of Computer Vision
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IEEE Transactions on Image Processing
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IEEE Computational Intelligence Magazine
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Proceedings of IEEE
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IEEE Signal Processing Magazine
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Neural Processing Letter
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Pattern Recognition
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Neural Networks
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ISPPRS Journal of Photogrammetry and Remote Sensing
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