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/icarofua/vehicle-rear

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Vehicle-Rear: A New Dataset to Explore Feature Fusion for Vehicle Identification Using Convolutional Neural Networks

https://github.com/ichbill/DQAS

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Dataset Quantization with Active Learning based Adaptive Sampling

https://github.com/idejie/KAD

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Active Object Detection with Knowledge Aggregation and Distillation from Large Models

https://github.com/idramalab/pixelmod

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PIXELMOD: Improving Soft Moderation of Visual Misleading Information on Twitter

https://github.com/ielab/goldilocks-reproduce

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A Reproducibility Study of Goldilocks: Just-Right Tuning of BERT for TAR

https://github.com/ies-research/multi-annotator-machine-learning

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dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans

https://github.com/ihsaan-ullah/meta-album

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Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification

https://github.com/ihsanullah2131/meta-album

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Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification

https://github.com/imatge-upc/medical-2017-nipsw

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Cost-Effective Active Learning for Melanoma Segmentation

https://github.com/iminthemiddle/vatl4pose-wacv2024

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Active Transfer Learning for Efficient Video-Specific Human Pose Estimation

https://github.com/iml-dkfz/realistic-al

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Navigating the Pitfalls of Active Learning Evaluation: A Systematic Framework for Meaningful Performance Assessment

https://github.com/iml-dkfz/values

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ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation

https://github.com/immuno121/als4gan

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Active Learning for Improved Semi-Supervised Semantic Segmentation in Satellite Images

https://github.com/indian-nlp/assamese-dataset

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Enhancing Assamese NLP Capabilities: Introducing a Centralized Dataset Repository

https://github.com/industryessentials/ymir

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YMIR: A Rapid Data-centric Development Platform for Vision Applications

https://github.com/instdin/institutional-books-1-pipeline

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Institutional Books 1.0: A 242B token dataset from Harvard Library's collections, refined for accuracy and usability

https://github.com/iosband/ts_tutorial

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A Tutorial on Thompson Sampling

https://github.com/ipcng00/ldm-s

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Querying Easily Flip-flopped Samples for Deep Active Learning

https://github.com/ipeis/HH-VAEM

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Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo

https://github.com/isayev/ASE_ANI

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Less is more: sampling chemical space with active learning

https://github.com/isayev/COMP6

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Less is more: sampling chemical space with active learning

https://github.com/ispamm/naf-dpm

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NAF-DPM: A Nonlinear Activation-Free Diffusion Probabilistic Model for Document Enhancement

https://github.com/ivadomed/model-spinal-rootlets

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Automatic Segmentation of the Spinal Cord Nerve Rootlets

https://github.com/j-rausch/dsg

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DSG: An End-to-End Document Structure Generator

https://github.com/jackieam/gvi-best-path

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Analyzing Green View Index and Green View Index best path using Google Street View and deep learning

https://github.com/jacob-thrasher/AL-OCTA

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Enhancing Retinal Disease Classification from OCTA Images via Active Learning Techniques

https://github.com/jacobtyo/swintextspotter

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Reading Between the Mud: A Challenging Motorcycle Racer Number Dataset

https://github.com/jacobzhaoziyuan/DSAL

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DSAL: Deeply Supervised Active Learning from Strong and Weak Labelers for Biomedical Image Segmentation

https://github.com/jacobzhaoziyuan/SAAL

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Self-supervised Assisted Active Learning for Skin Lesion Segmentation

https://github.com/jaeohwoo/balancedentropy

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Active Learning in Bayesian Neural Networks with Balanced Entropy Learning Principle

https://github.com/janelia-flyem/gala

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Machine learning of hierarchical clustering to segment 2D and 3D images

https://github.com/jarobyte91/post_ocr_correction

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Post-OCR Document Correction with large Ensembles of Character Sequence-to-Sequence Models

https://github.com/jasonkim8652/al_breakdown

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Understanding active learning of molecular docking and its applications

https://github.com/javadzb/class-balanced-al

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Class-Balanced Active Learning for Image Classification

https://github.com/jbaudru/llm-ocr-htr-historical-text-recognition

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Early evidence of how LLMs outperform traditional systems on OCR/HTR tasks for historical records

https://github.com/jdkuhnke/hic

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Image-based Detection of Surface Defects in Concrete during Construction

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