Multi-culture Sign Language Detection and Recognition Using Fine-tuned Convolutional Neural Network-Reference-Cited by-同舟云学术

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Multi-culture Sign Language Detection and Recognition Using Fine-tuned Convolutional Neural Network

Published:2023-02-05 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Smart Computing and Application (ICSCA)
language:
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Author:

Nurnoby M Faisal¹,El-Alfy El-Sayed M.²

Affiliation:

1. King Fahd University of Petroleum & Minerals (KFUPM),Information and Computer Science,Saudi Arabia

2. SDAIA-KFUPM Joint Research Center for Artificial Intelligence (JRC-AI), *Affiliate, Interdisciplinary Research Center for Intelligent Secure Systems (IRC-ISS), KFUPM

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10087341/10087376/10087884.pdf?arnumber=10087884

Reference32 articles.

1. A Signer-Independent Sign Language Recognition System Based on the Weighted KNN/HMM

2. Spelling it out: Real-time ASL fingerspelling recognition

3. Multi-objective optimization for hand posture recognition

4. Video-based signer-independent Arabic sign language recognition using hidden Markov models

5. Improving neural networks by preventing co-adaptation of feature detectors;hinton;ArXiv Preprint,2012

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. Hand Gesture Recognition for Multi-Culture Sign Language Using Graph and General Deep Learning Network;IEEE Open Journal of the Computer Society;2024

2. Detection of Indian Regional Sign Language Through Convolutional Neural Network;2023 Global Conference on Information Technologies and Communications (GCITC);2023-12-01

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