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/jellychen7/alemo

공식 코드

Machine Learning-Accelerated Multi-Objective Design of Fractured Geothermal Systems

https://github.com/jfkuang/cfam

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Visual Information Extraction in the Wild: Practical Dataset and End-to-end Solution

https://github.com/jgonsior/DS22-ImitAL

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ImitAL: Learned Active Learning Strategy on Synthetic Data

https://github.com/jgonsior/ImitAL

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ImitAL: Learning Active Learning Strategies from Synthetic Data

https://github.com/jgonsior/btw-softmax-clipping

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To Softmax, or not to Softmax: that is the question when applying Active Learning for Transformer Models

https://github.com/jgonsior/olympic-games-of-active-learning

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Survey of Active Learning Hyperparameters: Insights from a Large-Scale Experimental Grid

https://github.com/jiangnanhugo/apps-ode

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Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching

https://github.com/jiayichen815/feal

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Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts

https://github.com/jiayou-chao/multi-domain-ocr

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Efficient Multi-domain Text Recognition Deep Neural Network Parameterization with Residual Adapters

https://github.com/jiezou0806/SBSTAR

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Technology Assisted Reviews: Finding the Last Few Relevant Documents by Asking Yes/No Questions to Reviewers

https://github.com/jifanz/GALAXY

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GALAXY: Graph-based Active Learning at the Extreme

https://github.com/jifanz/tailor

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Algorithm Selection for Deep Active Learning with Imbalanced Datasets

https://github.com/jilljenn/vae

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Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems

https://github.com/jinchaogjc/esa

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ESA: Annotation-Efficient Active Learning for Semantic Segmentation

https://github.com/jiuhaichen/florence-vl

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Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth Fusion

https://github.com/jjzha/cal

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Cartography Active Learning

https://github.com/jlko/active-surrogate-estimators

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Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation

https://github.com/jlko/active-testing

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Active Testing: Sample-Efficient Model Evaluation

https://github.com/jmandivarapu1/Deep-Active-Learning-via-Open-Set-Recognition

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Deep Active Learning via Open Set Recognition

https://github.com/jnzju/coti

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Controllable Textual Inversion for Personalized Text-to-Image Generation

https://github.com/jo-pan/flowlearn

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FlowLearn: Evaluating Large Vision-Language Models on Flowchart Understanding

https://github.com/joanrod/ocr-vqgan

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OCR-VQGAN: Taming Text-within-Image Generation

https://github.com/joanrod/paper2figure-dataset

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OCR-VQGAN: Taming Text-within-Image Generation

https://github.com/joerntebbe/safetybounds4gpinal

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Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning

https://github.com/joeynmt/joeynmt

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Self-Regulated Interactive Sequence-to-Sequence Learning

https://github.com/johnmartinsson/adaptive-change-point-detection

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From Weak to Strong Sound Event Labels using Adaptive Change-Point Detection and Active Learning

https://github.com/johnsk95/pt4al

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PT4AL: Using Self-Supervised Pretext Tasks for Active Learning

https://github.com/joisino/seafaring

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Active Learning from the Web

https://github.com/jonaselgammal/gpry

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Fast and robust Bayesian Inference using Gaussian Processes with GPry

https://github.com/jonhue/activeft

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Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs

https://github.com/jonzarecki/textual-membership-queries

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Textual Membership Queries

https://github.com/jonzarecki/textual-mqs

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Textual Membership Queries

https://github.com/joshuajano/DBEST

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On Manipulating Scene Text in the Wild with Diffusion Models

https://github.com/josipjukic/adapter-al

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Parameter-Efficient Language Model Tuning with Active Learning in Low-Resource Settings

https://github.com/jpfolch/catechol_solvent_selection

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The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning

https://github.com/juangamella/abcd

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Active Invariant Causal Prediction: Experiment Selection through Stability

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