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Handwriting Verification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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The goal of handwriting verification is to find a measure of confidence whether the given handwritten samples are written by the same or different writer.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
DPCSpell: A Transformer-based Detector-Purificator-Corrector Framework for Spelling Error Correction of Bangla and Resource Scarce Indic Languages
MSDS: A Large-Scale Chinese Signature and Token Digit String Dataset for Handwriting Verification
Spelling Correction with Denoising Transformer
Attention based Writer Independent Handwriting Verification
Explanation based Handwriting Verification
Hybrid Feature Learning for Handwriting Verification
SigNet: Convolutional Siamese Network for Writer Independent Offline Signature Verification
Convolutional Sequence to Sequence Learning
Neural Machine Translation by Jointly Learning to Align and Translate
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.