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/wernerth94/bayesian-active-learning-by-distribution-disagreement

공식 코드

Bayesian Active Learning By Distribution Disagreement

https://github.com/whlscut/DocLayLLM

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DocLayLLM: An Efficient and Effective Multi-modal Extension of Large Language Models for Text-rich Document Understanding

https://github.com/whq-xxh/sfada-uwf-slo

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Advancing UWF-SLO Vessel Segmentation with Source-Free Active Domain Adaptation and a Novel Multi-Center Dataset

https://github.com/withchencheng/ecml_pkdd_23_real

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REAL: A Representative Error-Driven Approach for Active Learning

https://github.com/wjmaddox/online_vargp

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Conditioning Sparse Variational Gaussian Processes for Online Decision-making

https://github.com/wolfgarbe/symspell

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German Parliamentary Corpus (GerParCor)

https://github.com/wormgit/labelaherdinminutes

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Label a Herd in Minutes: Individual Holstein-Friesian Cattle Identification

https://github.com/wzk1015/CNMT

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Confidence-aware Non-repetitive Multimodal Transformers for TextCaps

https://github.com/wzx99/clipocr

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Symmetrical Linguistic Feature Distillation with CLIP for Scene Text Recognition

https://github.com/x-plug/mplug-docowl

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mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding

https://github.com/xbraininc/viraal

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VirAAL: Virtual Adversarial Active Learning For NLU

https://github.com/xcsf-dev/xcsf

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Deep Learning with a Classifier System: Initial Results

https://github.com/xfyna/al-bnn-gp

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Comparing Active Learning Performance Driven by Gaussian Processes or Bayesian Neural Networks for Constrained Trajectory Exploration

https://github.com/xiangyan93/molecules-enumerate

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Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular Simulation

https://github.com/xiaojino/RUArt

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RUArt: A Novel Text-Centered Solution for Text-Based Visual Question Answering

https://github.com/xkianteb/leaqi

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Active Imitation Learning with Noisy Guidance

https://github.com/xmichelleshihx/AL-LRTD

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LRTD: Long-Range Temporal Dependency based Active Learning for Surgical Workflow Recognition

https://github.com/xmichelleshihx/AL_Skin_SAAS

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An Active Learning Approach for Reducing Annotation Cost in Skin Lesion Analysis

https://github.com/xqh19970407/invdesflow-al

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InvDesFlow-AL: Active Learning-based Workflow for Inverse Design of Functional Materials

https://github.com/xulabs/aitom

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Boosting Active Learning via Improving Test Performance

https://github.com/xuyangabert/alcs

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Mitigating shortage of labeled data using clustering-based active learning with diversity exploration

https://github.com/yangarbiter/multilabel-learn

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Cost-Sensitive Reference Pair Encoding for Multi-Label Learning

https://github.com/yanhuiailab/rdss

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Enhancing Semi-Supervised Learning via Representative and Diverse Sample Selection

https://github.com/yash0307/E2E-MLT

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E2E-MLT - an Unconstrained End-to-End Method for Multi-Language Scene Text

https://github.com/yashkant/sam-textvqa

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Spatially Aware Multimodal Transformers for TextVQA

https://github.com/yazdaniamir38/madbal

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Maturity-Aware Active Learning for Semantic Segmentation with Hierarchically-Adaptive Sample Assessment

https://github.com/ycao5602/kafal

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Knowledge-Aware Federated Active Learning with Non-IID Data

https://github.com/yichen928/freesel

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Towards Free Data Selection with General-Purpose Models

https://github.com/yichen928/geal_active_learning

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Towards General and Efficient Active Learning

https://github.com/yikeqicn/DeepErase

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DeepErase: Weakly Supervised Ink Artifact Removal in Document Text Images

https://github.com/yilingjia/ActSense

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Active Collaborative Sensing for Energy Breakdown

https://github.com/yiye3/guicourse

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GUICourse: From General Vision Language Models to Versatile GUI Agents

https://github.com/yrahul3910/adaptive-lr-dnn

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LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence

https://github.com/ysig/learnable-typewriter

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The Learnable Typewriter: A Generative Approach to Text Analysis

https://github.com/yuanchen-wu/robustactivelearning

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Robust Offline Active Learning on Graphs

https://github.com/yuantn/MI-AOD

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Multiple instance active learning for object detection

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