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/explainableml/probvlm

공식 코드

ProbVLM: Probabilistic Adapter for Frozen Vision-Language Models

https://github.com/eyalbd2/scratchda

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Domain Adaptation from Scratch

https://github.com/facebookresearch/MultiplexedOCR

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A Multiplexed Network for End-to-End, Multilingual OCR

https://github.com/facebookresearch/adaptiveweightsampling

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On the Convergence of Loss and Uncertainty-based Active Learning Algorithms

https://github.com/facebookresearch/gtn_applications/blob/main/criterions/stc.py

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Star Temporal Classification: Sequence Classification with Partially Labeled Data

https://github.com/facebookresearch/multi_view_active_learning

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Rethinking the Data Annotation Process for Multi-view 3D Pose Estimation with Active Learning and Self-Training

https://github.com/facebookresearch/nougat

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Nougat: Neural Optical Understanding for Academic Documents

https://github.com/factodeeplearning/dan

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DAN: a Segmentation-free Document Attention Network for Handwritten Document Recognition

https://github.com/factodeeplearning/fasterdan

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Faster DAN: Multi-target Queries with Document Positional Encoding for End-to-end Handwritten Document Recognition

https://github.com/factodeeplearning/meta_dan

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Meta-DAN: towards an efficient prediction strategy for page-level handwritten text recognition

https://github.com/fahim-sikder/Bangla-Digit-Generation-GAN

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Bangla Handwritten Digit Recognition and Generation

https://github.com/fangbufang/sal

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Separate and Locate: Rethink the Text in Text-based Visual Question Answering

https://github.com/fastmachinelearning/hls4ml

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Compressing deep neural networks on FPGAs to binary and ternary precision with HLS4ML

https://github.com/fastread/src

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Finding Better Active Learners for Faster Literature Reviews

https://github.com/fbickfordsmith/epig

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Prediction-Oriented Bayesian Active Learning

https://github.com/feedzai/research-aml-elliptic

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Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity

https://github.com/feup-infolab/archmine

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Optimization of Image Processing Algorithms for Character Recognition in Cultural Typewritten Documents

https://github.com/fh2019ustc/DocScanner

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DocScanner: Robust Document Image Rectification with Progressive Learning

https://github.com/fh2019ustc/doctr

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DocTr: Document Image Transformer for Geometric Unwarping and Illumination Correction

https://github.com/fiveai/hgp_experiments

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An Active Learning Reliability Method for Systems with Partially Defined Performance Functions

https://github.com/fivosts/BenchPress

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BenchPress: A Deep Active Benchmark Generator

https://github.com/fjelenic/al-transfer

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On Dataset Transferability in Active Learning for Transformers

https://github.com/fjxmlzn/raregan

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RareGAN: Generating Samples for Rare Classes

https://github.com/flyingfeather/dea-sql

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Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm

https://github.com/foadsohrabi/dl-activesensing

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Active Sensing for Communications by Learning

https://github.com/for-ai/iterative-data-selection

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Diversify and Conquer: Diversity-Centric Data Selection with Iterative Refinement

https://github.com/forest-snow/alps

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Cold-start Active Learning through Self-supervised Language Modeling

https://github.com/forest-snow/clime-ui

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Interactive Refinement of Cross-Lingual Word Embeddings

https://github.com/forest-snow/incremental-coref

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Adapting Coreference Resolution Models through Active Learning

https://github.com/foundation-multimodal-models/world2code

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World to Code: Multi-modal Data Generation via Self-Instructed Compositional Captioning and Filtering

https://github.com/fpv-iplab/MECCANO

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The MECCANO Dataset: Understanding Human-Object Interactions from Egocentric Videos in an Industrial-like Domain

https://github.com/francescacairoli/stoch_nsc

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Neural Predictive Monitoring under Partial Observability

https://github.com/francescotonini/al-gtd

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AL-GTD: Deep Active Learning for Gaze Target Detection

https://github.com/franklinnwren/ds-age

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Dissimilar Nodes Improve Graph Active Learning

https://github.com/fsahli/MFclass

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Multi-fidelity classification using Gaussian processes: accelerating the prediction of large-scale computational models

https://github.com/fudannlplab/mousi

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MouSi: Poly-Visual-Expert Vision-Language Models

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