Most of the time, people use different deep learning frameworks and standard development toolkits. (SDKs), which are used to implement deep learning methods, are as follows:
frame
- Tensorflow: https://www.tensorflow.org/
- Caffe: http://caffe.berkeleyvision.org/
- KERAS: https://keras.io/
- Theano: http://deeplearning.net/softw…
- Torch: http://torch.ch/
- PyTorch: http://pytorch.org/
- Lasagne: https://lasagne.readthedocs.i…
- DL4J (DeepLearning4J): https://deeplearning4j.org/
- Chainer: http://chainer.org/
- DIGITS: https://developer.nvidia.com/…
- CNTK (Microsoft): https://github.com/Microsoft/…
- MatConvNet: http://www.vlfeat.org/matconv…
- MINERVA: https://github.com/dmlc/minerva
- MXNET: https://github.com/dmlc/mxnet
- OpenDeep: http://www.opendeep.org/
- PuRine: https://github.com/purine/pur…
- PyLerarn2: http://deeplearning.net/softw…
- TensorLayer: https://github.com/zsdonghao/…
- LBANN: https://github.com/LLNL/lbann
SDKs
- cuDNN: https://developer.nvidia.com/…
- TensorRT: https://developer.nvidia.com/…
- DeepStreamSDK: https://developer.nvidia.com/…
- cuBLAS: https://developer.nvidia.com/…
- cuSPARSE: http://docs.nvidia.com/cuda/c…
- NCCL : https://devblogs.nvidia.com/p…
Benchmark dataset
The following is a list of benchmark datasets commonly used to evaluate deep learning methods in different application areas.
Image classification or detection or segmentation
- MNIST: http://yann.lecun.com/exdb/mn…
- CIFAR 10/100: https://www.cs.toronto.edu/~k…
- SVHN/ SVHN2: http://ufldl.stanford.edu/hou…
- CalTech 101/256: http://www.vision.caltech.edu…
- STL-10: https://cs.stanford.edu/~acoa…
- NORB: http://www.cs.nyu.edu/~ylclab…
- SUN-dataset: http://groups.csail.mit.edu/v…
- ImageNet: http://www.image-net.org/
- National Data Science Bowl Competition: http://www.datasciencebowl.com/
- COIL 20/100: http://www.cs.columbia.edu/CA…
- MS COCO DATASET: http://mscoco.org/
- MIT-67 scene dataset: http://web.mit.edu/torralba/w…
- Caltech-UCSD Birds-200 dataset: http://www.vision.caltech.edu…
2011.html
- Pascal VOC 2007 dataset: http://host.robots.ox.ac.uk/p…
- H3D Human Attributes dataset:
https://www2.eecs.berkeley.ed…
- Face recognition dataset: http://vis-www.cs.umass.edu/lfw/
- For more data-set visit: https://www.kaggle.com/
- http://homepages.inf.ed.ac.uk…
- Recently Introduced Datasets in Sept. 2016:
- Google Open Images (~9M images)—https://github.com/openimages…
- Youtube-8M (8M videos: https://research.google.com/y…
Text classification
- Reuters-21578 Text Categorization Collection:
http://kdd.ics.uci.edu/databa…
- Sentiment analysis from Stanford: http://ai.stanford.edu/~amaas…
- Movie sentiment analysis from Cornel:
http://www.cs.cornell.edu/peo…
Free eBooks: https://www.gutenberg.org/
- Brown and stanford corpus on present americal english:
https://en.wikipedia.org/wiki…
- Google 1Billion word corpus: https://github.com/ciprian-ch…
modeling-benchmark
image encoding
- Flickr-8k: http://nlp.cs.illinois.edu/Ho…
- Common Objects in Context (COCO):http://cocodataset.org/#overview；http://sidgan.me/technical/2016/01/09/Exploring-Datasets
MT
–Pairs of sentences in English and French: https://www.isi.edu/naturalla…
download/hansard/
- European Parliament Proceedings parallel Corpus 196-2011:
http://www.statmt.org/europarl/
- The statistics for machine translation: http://www.statmt.org/
Q & A
- Stanford Question Answering Dataset (SQuAD): https://rajpurkar.github.io/S…
- Dataset from DeepMind: https://github.com/deepmind/r…
- Amazon dataset:http://jmcauley.ucsd.edu/data…；http://trec.nist.gov/data/qamain…,；http://www.ark.cs.cmu.edu/QA-…；http://webscope.sandbox.yahoo.co…,；http://blog.stackoverflow.com…
Speech recognition
- TIMIT : https://catalog.ldc.upenn.edu…
- Voxforge: http://voxforge.org/
- Open Speech and Language Resources: http://www.openslr.org/12/
Abstract
- https://archive.ics.uci.edu/m…
- http://www-nlpir.nist.gov/rel…
- https://catalog.ldc.upenn.edu…
Emotional analysis
- IMDB dataset: http://www.imdb.com/
Hyperspectral image analysis
- http://www.ehu.eus/ccwintco/i…
- https://engineering.purdue.ed…
- http://www2.isprs.org/commiss…
Journals and conferences
Conferences
- Neural Information Processing System (NIPS)
- International Conference on Learning Representation (ICLR): What are you doing for
Deep Learning?
- International Conference on Machine Learning (ICML)
- Computer Vision and Pattern Recognition (CVPR): What are you doing with Deep
Learning?
- International Conference on Computer Vision (ICCV)
- European Conference on Computer Vision (ECCV)
- British Machine Vision Conference (BMVC)
Journal
- Journal of Machine Learning Research (JMLR)
- IEEE Transaction of Neural Network and Learning System (
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- Computer Vision and Image Understanding (CVIU)
- Pattern Recognition Letter
- Neural Computing and Application
- International Journal of Computer Vision
- IEEE Transactions on Image Processing
- IEEE Computational Intelligence Magazine
- Proceedings of IEEE
- IEEE Signal Processing Magazine
- Neural Processing Letter
- Pattern Recognition
- Neural Networks
- ISPPRS Journal of Photogrammetry and Remote Sensing