AttentionHTR: Handwritten Text Recognition Based on Attention Encoder-Decoder Networks

Dmitrijs Kass; Ekta Vats

doi:10.1007/978-3-031-06555-2_34

ScienceGate Book Chapters

BOOK-CHAPTER

AttentionHTR: Handwritten Text Recognition Based on Attention Encoder-Decoder Networks

Dmitrijs Kass Ekta Vats

Year: 2022 Lecture notes in computer science Pages: 507-522 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-031-06555-2_34

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Encoder Handwriting Artificial intelligence Speech recognition Sequence (biology) Feature (linguistics) Pattern recognition (psychology) Word (group theory) Feature extraction Decoding methods Source code Natural language processing Algorithm

Metrics

Cited By

6.45

FWCI (Field Weighted Citation Impact)

Refs

0.96

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Handwritten Text Recognition Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Natural Language Processing Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Image Processing and 3D Reconstruction

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

AttentionHTR: Handwritten Text Recognition Based on Attention Encoder-Decoder Networks

Metrics

Citation History

Topics

Related Documents

Attention-based encoder-decoder networks for workflow recognition

Enhanced Attention-Based Encoder-Decoder Framework for Text Recognition

Gated Convolution and Stacked Self-Attention Encoder–Decoder-Based Model for Offline Handwritten Ethiopic Text Recognition

SwinArabert: An Encoder-Decoder Approach for Arabic Handwritten Text Recognition

Multiple attention-based encoder–decoder networks for gas meter character recognition