Papers with Code 아카이브

Optical Character Recognition (OCR)

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하위 태스크: 10
평가표: 6
보존된 평가 기록: 20

Optical Character Recognition or Optical Character Reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text on signs and billboards in a landscape photo, license plates in cars...) or from subtitle text superimposed on an image (for example: from a television broadcast)

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/raychiu0202/paddleOCR_flask

PP-OCR: A Practical Ultra Lightweight OCR System

https://github.com/rgreenblatt/ai_alignment_readings

Cooperative Inverse Reinforcement Learning

https://github.com/rickyHong/CRNN-Tensorflow-Text-repl

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/rle-foundation/rlexplore

Self-Supervised Exploration via Disagreement

https://github.com/rproskuryakov/ai-journey-2020

Trainable Spectrally Initializable Matrix Transformations in Convolutional Neural Networks

https://github.com/rubenpt91/pfl-docvqa-competition

Privacy-Aware Document Visual Question Answering

https://github.com/sahamath/SYM-Net

LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence

https://github.com/sahamath/sym-netv1

LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence

https://github.com/saleml/gfn

GFlowNet Foundations

https://github.com/saleml/torchgfn

GFlowNet Foundations

https://github.com/samueltin/tf-crnn_backup20180808

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/sartaj0/TextRecognition-Pytorch

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/sberbank-ai/digital_peter_aij2020

Digital Peter: Dataset, Competition and Handwriting Recognition Methods

https://github.com/sbillburg/CRNN-with-STN

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/sbu-dsl/ocr-detection

Cleaning Dirty Books: Post-OCR Processing for Previously Scanned Texts

https://github.com/scorebo/scorebo

Bayesian Active Learning with Fully Bayesian Gaussian Processes

https://github.com/sejong-rcv/OO4AL

Overcoming Overconfidence for Active Learning

https://github.com/senlinuc/caffe_ocr

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/seominseok0429/Learning-Loss-for-Active-Learning-Pytorch

Learning Loss for Active Learning

https://github.com/seonghwanseo/pharmaconet

TacoGFN: Target-conditioned GFlowNet for Structure-based Drug Design

https://github.com/servicenow/synbols

Synbols: Probing Learning Algorithms with Synthetic Datasets

https://github.com/sgenza/tf_crnn

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/sghong977/AL-consistency-based

Deep Active Learning with Augmentation-based Consistency Estimation

https://github.com/shivaverma/Score-Time-Detection

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/shreshtashetty/OCR

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/simpleintel/jupyter

Spatially-sparse convolutional neural networks

https://github.com/simplify23/Ultra_light_OCR_No.11

Manifold Mixup improves text recognition with CTC loss

https://github.com/sleep3r/garrus

Confidence-Aware Learning for Deep Neural Networks

https://github.com/smilelite/RobustScanner.paddle

RobustScanner: Dynamically Enhancing Positional Clues for Robust Text Recognition

https://github.com/solaris33/EAST-tf2

EAST: An Efficient and Accurate Scene Text Detector

https://github.com/solivr/tf-crnn

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/sonamghosh/local_hack_day_2018

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/songchujun/joeynmt

Self-Regulated Interactive Sequence-to-Sequence Learning

https://github.com/sooftware/OpenSpeech

Speech Recognition with Deep Recurrent Neural Networks

https://github.com/sparkfish/shabby-pages

DDI-100: Dataset for Text Detection and Recognition

https://github.com/stanford-futuredata/omg

Model Assertions for Monitoring and Improving ML Models

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.