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/meghshukla/activelearningforhumanpose

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Bayesian Uncertainty and Expected Gradient Length -- Regression: Two Sides Of The Same Coin?

https://github.com/meghshukla/math-analysis-learningloss

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A Mathematical Analysis of Learning Loss for Active Learning in Regression

https://github.com/mehrdad-dev/persis

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Persis: A Persian Font Recognition Pipeline Using Convolutional Neural Networks

https://github.com/mehreenmehreen/muharaf

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Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition

https://github.com/mehreenmehreen/start_follow_read_arabic

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Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition

https://github.com/meisin/crudeoilnews-corpus

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CrudeOilNews: An Annotated Crude Oil News Corpus for Event Extraction

https://github.com/melinphd/taal

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TAAL: Test-time Augmentation for Active Learning in Medical Image Segmentation

https://github.com/mengf1/PAL

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Learning how to Active Learn: A Deep Reinforcement Learning Approach

https://github.com/mengf1/trpos

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Model Transfer for Tagging Low-resource Languages using a Bilingual Dictionary

https://github.com/mengxiayu/coser

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Context Selection and Rewriting for Video-based Educational Question Generation

https://github.com/mesophil/myriadal

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MyriadAL: Active Few Shot Learning for Histopathology

https://github.com/metabrainagi/awaker

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Awaker2.5-VL: Stably Scaling MLLMs with Parameter-Efficient Mixture of Experts

https://github.com/mhumphries2323/Transcription_Pearl

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Unlocking the Archives: Using Large Language Models to Transcribe Handwritten Historical Documents

https://github.com/mic-dkfz/attractive_simulations

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atTRACTive: Semi-automatic white matter tract segmentation using active learning

https://github.com/miccaiif/openal

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OpenAL: An Efficient Deep Active Learning Framework for Open-Set Pathology Image Classification

https://github.com/microsoft/GenerativeImage2Text

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GIT: A Generative Image-to-text Transformer for Vision and Language

https://github.com/microsoft/TAP

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TAP: Text-Aware Pre-training for Text-VQA and Text-Caption

https://github.com/microsoft/TableSense

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TableSense: Spreadsheet Table Detection with Convolutional Neural Networks

https://github.com/microsoft/genalog

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Lights, Camera, Action! A Framework to Improve NLP Accuracy over OCR documents

https://github.com/microsoft/unilm

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LayoutReader: Pre-training of Text and Layout for Reading Order Detection

https://github.com/microsoft/unilm/tree/master/dit

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DiT: Self-supervised Pre-training for Document Image Transformer

https://github.com/microsoft/unilm/tree/master/trocr

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TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models

https://github.com/mikahama/natas

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From the Paft to the Fiiture: a Fully Automatic NMT and Word Embeddings Method for OCR Post-Correction

https://github.com/mila-iqia/DeepDrummer

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DeepDrummer : Generating Drum Loops using Deep Learning and a Human in the Loop

https://github.com/mililab/logicocr

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LogicOCR: Do Your Large Multimodal Models Excel at Logical Reasoning on Text-Rich Images?

https://github.com/millerk22/model-change-paper

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Model-Change Active Learning in Graph-Based Semi-Supervised Learning

https://github.com/millerk22/rwll_active_learning

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Poisson Reweighted Laplacian Uncertainty Sampling for Graph-based Active Learning

https://github.com/mingsun-tse/good-da-in-kd

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What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective

https://github.com/minhquan6203/vitextvqa-dataset

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ViTextVQA: A Large-Scale Visual Question Answering Dataset for Evaluating Vietnamese Text Comprehension in Images

https://github.com/minimel/stochasticbatchal

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Active learning for medical image segmentation with stochastic batches

https://github.com/minnesotanlp/infoverse

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infoVerse: A Universal Framework for Dataset Characterization with Multidimensional Meta-information

https://github.com/minnesotanlp/select-llm

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SelectLLM: Can LLMs Select Important Instructions to Annotate?

https://github.com/mir-group/flare

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Bayesian Force Fields from Active Learning for Simulation of Inter-Dimensional Transformation of Stanene

https://github.com/mir-group/nequip

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Fast Uncertainty Estimates in Deep Learning Interatomic Potentials

https://github.com/mirbostani/QA-KD-AL

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Improving Question Answering Performance Using Knowledge Distillation and Active Learning

https://github.com/mj10/bioseq-gfn-al

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Biological Sequence Design with GFlowNets

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