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/samsja/finding-a-needle-code

공식 코드

Improving traffic sign recognition by active search

https://github.com/samsungsailmontreal/stgg-al

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Generating $π$-Functional Molecules Using STGG+ with Active Learning

https://github.com/samuelstanton/conformal-bayesopt

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Bayesian Optimization with Conformal Prediction Sets

https://github.com/sanakhamekhem/GAN-HTR

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Enhance to Read Better: A Multi-Task Adversarial Network for Handwritten Document Image Enhancement

https://github.com/sanchit2843/Indian_LPR

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Indian Licence Plate Dataset in the wild

https://github.com/sangwoomo/gold

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Mining GOLD Samples for Conditional GANs

https://github.com/sanketx/al-foundation-models

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Revisiting Active Learning in the Era of Vision Foundation Models

https://github.com/sap-samples/clustertabnet

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ClusterTabNet: Supervised clustering method for table detection and table structure recognition

https://github.com/sasanvakili/Bayesian4Wiener

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Optimal Bayesian Affine Estimator and Active Learning for the Wiener Model

https://github.com/satoshi-kosugi/crowd-powered

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Crowd-Powered Photo Enhancement Featuring an Active Learning Based Local Filter

https://github.com/savya08/active-learning-on-heteroskedastic-distributions

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Neural Active Learning on Heteroskedastic Distributions

https://github.com/sbelharbi/deep-active-learning-for-joint-classification-and-segmentation-with-weak-annotator

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Deep Active Learning for Joint Classification & Segmentation with Weak Annotator

https://github.com/sberbank-ai/StackMix-OCR

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StackMix and Blot Augmentations for Handwritten Text Recognition

https://github.com/sberbank-ai/fusion_brain_aij2021

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Many Heads but One Brain: Fusion Brain -- a Competition and a Single Multimodal Multitask Architecture

https://github.com/scut-dlvclab/gpt-4v_ocr

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Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation

https://github.com/scut-dlvclab/megahan97k

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MegaHan97K: A Large-Scale Dataset for Mega-Category Chinese Character Recognition with over 97K Categories

https://github.com/sebastian-nehrdich/byt5-sanskrit-analyzers

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One Model is All You Need: ByT5-Sanskrit, a Unified Model for Sanskrit NLP Tasks

https://github.com/secondmind-labs/trieste

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Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow

https://github.com/sejong-rcv/2023.OO4AL

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Overcoming Overconfidence for Active Learning

https://github.com/seqam-lab/alwod

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ALWOD: Active Learning for Weakly-Supervised Object Detection

https://github.com/sergiocorreia/quipucamayoc

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Digitizing Historical Balance Sheet Data: A Practitioner's Guide

https://github.com/seuretm/combined-ocr

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Combining OCR Models for Reading Early Modern Printed Books

https://github.com/sgchr273/LPLgrad

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LPLgrad: Optimizing Active Learning Through Gradient Norm Sample Selection and Auxiliary Model Training

https://github.com/sgchr273/fishermask

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FisherMask: Enhancing Neural Network Labeling Efficiency in Image Classification Using Fisher Information

https://github.com/shajiayu1/OmniDataComposer

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OmniDataComposer: A Unified Data Structure for Multimodal Data Fusion and Infinite Data Generation

https://github.com/shamir-lab/rfan-trial

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Towards Regulatory-Confirmed Adaptive Clinical Trials: Machine Learning Opportunities and Solutions

https://github.com/shannanyinxiang/pagenet

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PageNet: Towards End-to-End Weakly Supervised Page-Level Handwritten Chinese Text Recognition

https://github.com/shaoncsecu/BN-HTR_LS

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BN-HTRd: A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR) and Line Segmentation

https://github.com/sharat29ag/CDAL

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Contextual Diversity for Active Learning

https://github.com/sharat29ag/contextual_class

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Reducing Annotation Effort by Identifying and Labeling Contextually Diverse Classes for Semantic Segmentation Under Domain Shift

https://github.com/shenkev/Caption-Lifetime-by-Asking-Questions

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Learning to Caption Images through a Lifetime by Asking Questions

https://github.com/shib0li/mra-fno

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Multi-Resolution Active Learning of Fourier Neural Operators

https://github.com/shichenqiao/ece554_sp23_fpga_handwriting_recognition

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FPGA Implementation of Convolutional Neural Network for Real-Time Handwriting Recognition

https://github.com/shijun18/paal-medseg

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Predictive Accuracy-Based Active Learning for Medical Image Segmentation

https://github.com/shizhediao/active-cot

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Active Prompting with Chain-of-Thought for Large Language Models

https://github.com/shizhediao/active-prompt

공식 코드

Active Prompting with Chain-of-Thought for Large Language Models

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