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://bitbucket.org/antonis/grikoresource

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Part-of-Speech Tagging on an Endangered Language: a Parallel Griko-Italian Resource

https://bitbucket.org/arahat/lod-2020

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On Bayesian Search for the Feasible Space Under Computationally Expensive Constraints

https://bitbucket.org/brown-data-science/georeg

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Mining Spatio-temporal Data on Industrialization from Historical Registries

https://bitbucket.org/gramacylab/deepgp-ex

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Active Learning for Deep Gaussian Process Surrogates

https://bitbucket.org/ispamm/group-lasso-deep-networks

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Group Sparse Regularization for Deep Neural Networks

https://bitbucket.org/smartan117/sgim-yumi-simu

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Intrinsically Motivated Open-Ended Multi-Task Learning Using Transfer Learning to Discover Task Hierarchy

https://github.com/000Justin000/ssl_edge

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Graph-based Semi-Supervised & Active Learning for Edge Flows

https://github.com/0liliulei/Mem3D

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Quality-Aware Memory Network for Interactive Volumetric Image Segmentation

https://github.com/0x454447415244/HandwritingRecognitionSystem

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Handwriting Recognition of Historical Documents with few labeled data

https://github.com/1170300714/cbs

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Class Balance Matters to Active Class-Incremental Learning

https://github.com/32af3611/ai4mat-neurips-workshop-2022

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Actively Learning Costly Reward Functions for Reinforcement Learning

https://github.com/AFeng-x/Draw-and-Understand

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Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Want

https://github.com/AI4Chem/ChemVlm

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ChemVLM: Exploring the Power of Multimodal Large Language Models in Chemistry Area

https://github.com/AICAN-Research/FAST-Pathology

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Code-free development and deployment of deep segmentation models for digital pathology

https://github.com/AIML-K/ActiveBayesianCausal

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ABC3: Active Bayesian Causal Inference with Cohn Criteria in Randomized Experiments

https://github.com/AP15/NeurIPS_2019

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Correlation Clustering with Adaptive Similarity Queries

https://github.com/AaltoML/BayesVLM

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Post-hoc Probabilistic Vision-Language Models

https://github.com/Aditi138/EntityTargetedActiveLearning

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A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity Recognizers

https://github.com/AhmedAyman911/LMV-RPA

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LMV-RPA: Large Model Voting-based Robotic Process Automation

https://github.com/AlibabaResearch/AdvancedLiterateMachinery/tree/main/OCR/LevOCR

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Levenshtein OCR

https://github.com/AlibabaResearch/AdvancedLiterateMachinery/tree/main/OCR/MGP-STR

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Multi-Granularity Prediction for Scene Text Recognition

https://github.com/ArantxaCasanova/ralis

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Reinforced active learning for image segmentation

https://github.com/ArjitJ/DIAL

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Deep Indexed Active Learning for Matching Heterogeneous Entity Representations

https://github.com/ArsamAryandoust/DataSelectionMaps

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Enhanced spatio-temporal electric load forecasts using less data with active deep learning

https://github.com/ArthurHoa/deep-eknn

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Reducing Aleatoric and Epistemic Uncertainty through Multi-modal Data Acquisition

https://github.com/AtiqueUrRehman/qaida

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Large Scale Font Independent Urdu Text Recognition System

https://github.com/BIT-AQH/Graph-Understanding-Multimodal-Benchmark

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When Graph Data Meets Multimodal: A New Paradigm for Graph Understanding and Reasoning

https://github.com/Bartzi/see

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SEE: Towards Semi-Supervised End-to-End Scene Text Recognition

https://github.com/Bartzi/stn-ocr

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STN-OCR: A single Neural Network for Text Detection and Text Recognition

https://github.com/BenGutteridge/judge-a-book

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Judge a Book by its Cover: Investigating Multi-Modal LLMs for Multi-Page Handwritten Document Transcription

https://github.com/BengaliAI/bbocr

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bbOCR: An Open-source Multi-domain OCR Pipeline for Bengali Documents

https://github.com/BengaliAI/graphemePrepare

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A Large Multi-Target Dataset of Common Bengali Handwritten Graphemes

https://github.com/Bidur-Khanal/imbalanced-medical-active-label-cleaning

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Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise

https://github.com/BjoernNieth/LS-Dataset-pruning-in-AT

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Large-Scale Dataset Pruning in Adversarial Training through Data Importance Extrapolation

https://github.com/BlackHC/BatchBALD

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BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning

https://github.com/BoChen-Daniel/Expert-Linking

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CODE: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking

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