Boosting ASL Communication with a Convolutional-Bidirectional LSTM Hybrid Model-Reference-Cited by-同舟云学术

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Boosting ASL Communication with a Convolutional-Bidirectional LSTM Hybrid Model

Published:2024-06-28 Issue: Volume:4 Page:1-5
ISSN:
Container-title:2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS)
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Author:

Madaan Vijay¹,Sharma Neha¹,Malhotra Sonal¹,Devliyal Swati²

Affiliation:

1. Chitkara University Institute of Engineering and Technology Chitkara University,Rajpura,Punjab,India

2. Computer Science & Engineering Graphic Era Deemed to be University,Dehradun,Uttarakhand,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10624684/10624740/10624846.pdf?arnumber=10624846

Reference16 articles.

1. Sign Language Fingerspelling Recognition using Synthetic Data;Fowley;AICS,2021

2. Finger spelled signs in sign language recognition using deep convolutional neural network;Rajendran;International Journal of Research in Engineering, Science and Management,2021

3. Proposed system for sign language recognition

4. Gesture Recognition Using Tensor flow, Opencv and Python;Sharma;Amity Journal of Computational Sciences,2023

5. An end-to-end Thai fingerspelling recognition frame-work with deep convolutional neural networks;Lata;ICIC Express Letters,2022

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