A Light-Weight Deep Learning-Based Architecture for Sign Language Classification-Reference-Cited by-同舟云学术

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A Light-Weight Deep Learning-Based Architecture for Sign Language Classification

Published:2023 Issue:3 Volume:35 Page:3501-3515
ISSN:1079-8587
Container-title:Intelligent Automation & Soft Computing
language:en
Short-container-title:

Author:

Daniel Nareshkumar M.,Jaison B.

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Software

Reference32 articles.

1. Akash Asl alphabet, Apr. 2018. [Online]. Available: https://www.kaggle.com/grassknoted/asl-alphabet.

2. R. Elakkiya and B. Natarajan, “Isl-csltr: Indian sign language dataset for continuous sign language translation and recognition,” Jan. 2021. [Online]. Available: https://data.mendeley.com/datasets/kcmpdxky7p/1.

3. Spelling it out: Real-time asl fingerspelling recognition;Pugeault,2011

4. Real time-based bare hand gesture recognition;Safaya;IPASJ International Journal of Information Technology,2013

5. A sinhala finger spelling interpretation system using nearest neighbor classification;Wathugala,2002

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Recent Advances on Deep Learning for Sign Language Recognition;Computer Modeling in Engineering & Sciences;2024

2. A Deep Learning Approach for Evaluating Children's Handwriting;Lecture Notes in Networks and Systems;2024

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