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/shrutirij/ocr-post-correction

공식 코드

OCR Post Correction for Endangered Language Texts

https://github.com/shubhomoydas/ad_examples

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Active Anomaly Detection via Ensembles

https://github.com/shuguoj/hsi-classification

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A Survey: Deep Learning for Hyperspectral Image Classification with Few Labeled Samples

https://github.com/shulk97/daniel

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DANIEL: A fast Document Attention Network for Information Extraction and Labelling of handwritten documents

https://github.com/shuvenduroy/activefer

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Active Learning with Contrastive Pre-training for Facial Expression Recognition

https://github.com/shuyansy/vidtext

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VidText: Towards Comprehensive Evaluation for Video Text Understanding

https://github.com/siddk/vqa-outliers

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Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering

https://github.com/simplify23/MRN

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MRN: Multiplexed Routing Network for Incremental Multilingual Text Recognition

https://github.com/simplify23/tps_pp

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TPS++: Attention-Enhanced Thin-Plate Spline for Scene Text Recognition

https://github.com/simula-complex/evoclinical

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EvoCLINICAL: Evolving Cyber-Cyber Digital Twin with Active Transfer Learning for Automated Cancer Registry System

https://github.com/sinhasam/vaal

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Variational Adversarial Active Learning

https://github.com/siplab-gt/APM-LR

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Feedback Coding for Active Learning

https://github.com/siyuhuang/TOD

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Semi-Supervised Active Learning with Temporal Output Discrepancy

https://github.com/slautin/2024_co-navigation

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Bayesian Co-navigation: Dynamic Designing of the Materials Digital Twins via Active Learning

https://github.com/slds-lmu/wildlife-experiments

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Automated wildlife image classification: An active learning tool for ecological applications

https://github.com/slds-lmu/wildlife-ml

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Automated wildlife image classification: An active learning tool for ecological applications

https://github.com/smallcube/EAL-GAN

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Supervised Anomaly Detection via Conditional Generative Adversarial Network and Ensemble Active Learning

https://github.com/smiletoe/hpal

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Hierarchical Point-based Active Learning for Semi-supervised Point Cloud Semantic Segmentation

https://github.com/smuradoglu/almorphinfl

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Eeny, meeny, miny, moe. How to choose data for morphological inflection

https://github.com/snova-jonathanl/hudocvqa

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Synthetic Document Question Answering in Hungarian

https://github.com/snu-mllab/greedypolicyformoco

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Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization

https://github.com/socialmediaie/pytail

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PyTAIL: Interactive and Incremental Learning of NLP Models with Human in the Loop for Online Data

https://github.com/sophiaalthammer/alforrankers

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Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection

https://github.com/soumyaxyz/abstractAnalysis

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Automatic Recognition of Learning Resource Category in a Digital Library

https://github.com/soumyaxyz/documentclassify

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Automatic Recognition of Learning Resource Category in a Digital Library

https://github.com/spectraldani/pai

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Parallel MCMC Without Embarrassing Failures

https://github.com/spirit-moon-fly/CAL

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Causal-Guided Active Learning for Debiasing Large Language Models

https://github.com/sprakbanken/nodalida25_sami_ocr

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Comparative analysis of optical character recognition methods for Sámi texts from the National Library of Norway

https://github.com/sprakbanken/synthetic_text_images

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Comparative analysis of optical character recognition methods for Sámi texts from the National Library of Norway

https://github.com/ssydasheng/predictive-correlation-benchmark

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Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?

https://github.com/stacs-cp/CP2024-Frugal

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Frugal Algorithm Selection

https://github.com/stamatisalex/ovenet

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OVeNet: Offset Vector Network for Semantic Segmentation

https://github.com/stanford-futuredata/selection-via-proxy

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Selection via Proxy: Efficient Data Selection for Deep Learning

https://github.com/stanfordasl/data-lifecycle-management

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Data Lifecycle Management in Evolving Input Distributions for Learning-based Aerospace Applications

https://github.com/stat-ml/large_batch_bald

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Scalable Batch Acquisition for Deep Bayesian Active Learning

https://github.com/stefan-it/historic-domain-adaptation-icdar

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Data Centric Domain Adaptation for Historical Text with OCR Errors

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