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1、PapersMulti-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networksintro:arxiv:. Ian J. GoodfellowEnd-to-End Text Recognition with Convolutional Neural Networkspaper:PhD thesis:Word Spotting and Recognition with Embedded Attributespaper:?arnumber=6857995&filter

2、%3DAND%28p_IS_Number%3A6940341%29Reading Text in the Wild with Convolutional Neural Networksarxiv:homepage:demo:code:Deep structured output learning for unconstrained text recognitionintro: "propose an architecture consisting of a character sequenceand an N-gram encodingwhichact on an input ima

3、ge in parallel and whose outputs are utilized along with a CRF m content present within the image."to recognize the textarxiv:Deep Features for Text Spottingpaper:bitbucket:gitxiv:Reading Scene Text in Deep Convolutional Sequencesarxiv:DeepFont: Identify Your Font from An Imagearxiv:An End-to-E

4、nd Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognitionintro: Convolutional Recurrent Neural Network (CRNN) arxiv:Recursive Recurrent Nets with Attention Marxiv:5557b4aeb1ce71a9fcfabde07a16f2aa52f5 · buiduchanh/Paper_giting for OCR in the W

5、ildWriter-independent Feature Learning for Offline Signature Verification using Deep Convolutional Neural Networksarxiv:DeepText: A Unified Framework for Text Proposal Generation and Text Detection in Natural Imagesarxiv:End-to-End Interpretation of the French Street Name Signs Datasetpaper:End-to-E

6、nd Subtitle Detection and Recognition for Near-Human-Level Performancearxiv:s in East Asian Languages viaEnsemble withSmart Library: Identifying Books in a Library using Richly Supervised Deep Scene Text Readingarxiv:Improving Text Proposals for Scene Images with Fully Convolutional Networksintro: U

7、niversitat Autonoma de Barcelona (UAB) & University of Florenceintro: International Conference on Pattern Recognition (ICPR) - DLPR (Deep Learning for Pattern Recognition) workshoparxiv:Scene Text EraserAttention-based Extraction of Structured Information from Street View Imageryintro: Universit

8、y College London & arxiv:IncSTN-OCR: A single Neural Network for Text Detection and Text Recognitionarxiv:(MXNet):Implicit Language Min LSTM for OCRSCAN: Sliding Convolutional Attention Network for Scene Text Recognition2/12Te2x018t/8/2D2 etectionPaper_git/2015-10-09-ocr.md at 907f5557b4aeb1ce71

9、a9fcfabde07a16f2aa52f5 · buiduchanh/Paper_gitObject Proposals for Text Extraction in the Wildintro: ICDAR 2015 arxiv:Text-Attentional Convolutional Neural Networks for Scene Text Detectionarxiv:Accurate Text Localization in Natural Image with Cascaded Convolutional Text Networkarxiv:Synthetic D

10、ata for Text Localisation in Natural Imagesintro: CVPR 2016 project page:arxiv:paper:Scene Text Detection via Holistic, Multi-Channel Predictionarxiv:Detecting Text in Natural Image with Connectionist Text Proposal Networkintro: ECCV 2016 arxiv:(Caffe):(CUDA8.0 support):demo:(Tensorflow):TextBoxes:

11、A Fast Text Detector with a Single Deep Neural Networkintro: AAAI 2017 arxiv:(Caffe):TextBoxes+: A Single-Shot Oriented Scene Text Detectorintro: TIP 2018. University of Science and Technology(HUST) arxiv:(official, Caffe):Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection3/12

12、2i0n1t8r/o8/:22CVPR 2017Paper_git/2015-10-09-ocr.md at 907f5557b4aeb1ce71a9fcfabde07a16f2aa52f5 · buiduchanh/Paper_gitintro: F-measure 70.64%, outperforming the existing state-of-the-art method with F-measure 63.76% arxiv:Detecting Oriented Text in Natural Images by Linking Segmentsintro: CVPR

13、2017 arxiv:(Tensorflow):Deep Direct Regression for Multi-Oriented Scene Text Detectionarxiv:Cascaded Segmentation-Detection Networks for Word-Level Text SpottingText-Detection-using-py-faster-r:-frameworkWordFence: Text Detection in Natural Images with Border Awarenessintro: ICIP 2017 arcxiv:SSD-tex

14、t detection: Text Detectorintro: A modified SSD m:R2: Rotational Regionfor text detectionfor Orientation Robust Scene Text Detectionintro: Samsung R&D Institute China arxiv:R-PHOC: Segmentation-Free Word Spotting usingintro: ICDAR 2017 arxiv:Towards End-to-end Text Spotting with Convolutional Re

15、current Neural NetworksEAST: An Efficient and Accurate Scene Text Detectorintro: CVPR 2017. Megvii arxiv:paper:(Tensorflow):Deep Scene Text Detection with Connected Component Proposalsintro: Amap Vision Lab, Alibaba Group4/122a0r1x8i/8v/:2-ocr.md at 907f5557b4aeb1ce71a9fcfabde07a16f2aa52f5 · bu

16、iduchanh/Paper_gitSingle Shot Text Detector with Regional Attentionintro: ICCV 2017 arxiv:code:Fused Text Segmentation Networks for Multi-oriented Scene Text DetectionDeep Residual Text Detection Network for Scene Textintro: IAPR International Conference on Document Analysis and Recognition (ICDAR)

17、2017. Samsung R&D Institute of China,arxiv:Feature Enhancement Network: A Refined Scene Text Detectorintro: AAAI 2018 arxiv:ArbiText: Arbitrary-Oriented Text Detection in Unconstrained SceneDetecting Curve Text in the Wild: New Dataset and New Solutionarxiv:FOTS: Fast Oriented Text Spotting with

18、 a Unified NetworkPixelLink: Detecting Scene Text via Instance Segmentationintro: AAAI 2018 arxiv:PixelLink: Detecting Scene Text via Instance Segmentationintro: AAAI 2018.arxiv:&Academy of SciencesSliding Line Point Regression for Shape Robust Scene Text DetectionSingle Shot TextSpotter with Ex

19、plicit Alignment and Attentionintro: CVPR 2018 arxiv:Rota5/122i0n1t8r/o8/:22CVPR 2018 arxiv:Detecting Multi-Oriented Text with Corner-based Region Proposalsarxiv:Paper_git/2015-10-09-ocr.md at 907f5557b4aeb1ce71a9fcfabde07a16f2aa52f5 · buiduchanh/Paper_gitAn Anchor-Free Region Proposal Network

20、for Faster R-based Text Detection ApproachesIncepText: A New Inception-Text Module with Deformable PSROI Pooling for Multi-Oriented Scene Text Detectionintro: IJCAI 2018. Alibaba Group arxiv:Boosting up Scene Text Detectors with GuidedShape Robust Text Detection with Progressive Scale Expansion Netw

21、orkarxiv:Text RecognitionSequence to sequence learning for unconstrained scene text recognitionintro: master thesis arxiv:Drawing and Recognizingarxiv:Characters with Recurrent Neural NetworkLearning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Text Reco

22、gnitionintro: correct rates: Dataset-CASIA 97.10% and Dataset-ICDAR 97.15% arxiv:Stroke Sequence-Dependent Deep Convolutional Neural Network for Online Handwritten Recognitionarxiv:CharacterVisual attention ms for scene text recognitionFocusing Attention: Towards Accurate Text Recognition in Natural

23、 Images6/122a0r1x8i/8v/:2-ocr.md at 907f5557b4aeb1ce71a9fcfabde07a16f2aa52f5 · buiduchanh/Paper_gitScene Text Recognition with Sliding Convolutional Character MsAdaDNNs: Adaptive Ensemble of Deep Neural Networks for Scene Text RecognitionA New Hybrid-parameter Recurrent Neural Networks for Onli

24、ne HandwrittenCharacter RecognitionArbitrarily-Oriented Text Recognitionintro: A method used in ICDAR 2017 word recognition competitions arxiv:SEE: Towards Semi-Supervised End-to-End Scene Text R/abs/1712.05404Edit Probability for Scene Text Recognitionintro: Fudan University & H

25、ikvision Research Institute arxiv:Breaking CaptchaUsing deep learning to break a Captcha systemintro: "Using Torch code to break simplecaptcha with 92% accuracy" blog:Breaking reddit captcha with 96% accuracyblog:Im not a human: Breaking thepaper:-reCAPTCHA-wp.pdfNeural Net CAPTCHA Cracker

26、slides:%20PDF:demo:reCAPTCHARecurrent neural networks for decoding CAPTCHAS7/122b01lo8/g8/:2demo:code:Reading irctc captchas with 95% accuracy using deep learning:端到端的OCR：基于blog:的實現(xiàn)I Am Robot: (Deep) Learning to Break Semantic Image CAPTCHAsintro: automatically solving 70.78% of the image reCaptchac

27、hallenges, while requiring only 19 seconds perchallenge. apply to the paper:SimGAN-Captchaimage captcha and achieve an accuracy of 83.5%intro: Solve captcha without manually labeling a training set:Handwritten RecognitionHigh Performance Offline Handwritten Feature Mapsarxiv:Recognize your handwritt

28、en numbersCharacter Recognition UsingNet and DirectionalHandwritten Digit Recognition using Convolutional Neural Networks in Python with Kerasblog:networks-python-keras/MNIST Handwritten Digit Classifier:如何用卷積神經(jīng)網(wǎng)絡(luò)blog:識別手寫數(shù)字集？LeNet Convolutional Neural Network in Pythonblog:Scan, Attend and Read: En

29、d-to-End Handwritten Paragraph Recognition with MDLSTM Attentionarxiv:8/12MLP2a0i1n8/t8:/2t2he Real-Time HanPdapwerr_igtitt/e20n15D-1i0g-0it9-oRcer mcod gatn9i0z7ef5r557b4aeb1ce71a9fcfabde07a16f2aa52f5 · buiduchanh/Paper_gitblog:demo:Training a Computer to Recognize Your HandwritingUsing Tensor

30、Flow to create your own handwriting recognition engineblog:Building a Deep Handwritten Digits Classifier using Microsoft Cognitive Toolkitblog:toolkit-6ae966caec69#.c3h6o7oxf:gym/blob/a97936619cf56b5ed43329c6fa13f7e26b1d46b8/MNIST/minist_softmax_cntk.pyHand Writing Recognition Using Convolutional Ne

31、ural Networksintro: This-based mfor recognition of hand written digits attains a validation accuracy of 99.2% aftertraining for 12 epochs. Its trained on the MNIST dataset on Kaggle.:Design of a Very CompactClassifier for Online HandwrittenCharacter Recognition UsingDropWeight and Global Poolingintr

32、o: 0.57 MB, performance is decreased only by 0.91%. arxiv:Handwritten digit string recognition by combination of residual network and RNN-CTCPlate RecognitionReading Car License Plates Using Deep Convolutional Neural Networks and LSTMsarxiv:Number plate recognition with Tensorflowblog:(Deep ANPR):en

33、d-to-end-for-plate-recognition:9/12Segm201e8n/8t/a22tion-free Vehicle PLaicpeern_gsite/20P1l5a-1t0e-0R9-eoccro.mgdnaitt9i0o7nf55u5s7bin4agebC1coen71vaN9fcefat-bRdeN07Na16f2aa52f5 · buiduchanh/Paper_gitintro: International Workshop on Advanced Image Technology, January, 8-10, 2017. Penang, Malay

34、sia.Proceeding IWAIT2017 arxiv:License Plate Detection and Recognition Using Deeply Learned Convolutional Neural Networksarxiv:api:Adversarial Generation of Training Examples for Vehicle License Plate RecognitionTowards End-to-End Car License Plates Detection and Recognition with Deep Neural Network

35、sHigh AccuracyPlate Recognition Frameworkintro: 基于深度學(xué)習(xí)高性能中文車牌識別 High Performancegihtub:LPRNet: License Plate Recognition via Deep Neural Networksintrp=o: Intel IOTG Computer Vision GroupLicense Plate Recognition Fro: works in real-time with recognition accuracy up to 95% forlicense plate

36、s: 3 ms/plate onnVIDIAR GeForceTMGTX 1080 and 1.3 ms/plate on IntelR CoreTMi7-6700K CPU.arxiv:BlogsApplying OCR Technology for Receipt Recognitionblog:mirror:Hacking MNIST in 30 lines of Pythonblog:Optical Character Recognition Using One-Shot Learning, RNN, and TensorFlowCreating a Modern OCR Pipeline Using Computer Vision and Deep Learninglearning/Projects10/122018/8/22Paper_git/2015-10-09-ocr.md at 907f5557b4aeb1ce71a9fc