Mexican Sign Language Recognition Using Jacobi-Fourier Moments

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ISSN Print: 1947-3931
ISSN Online: 1947-394X
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"Mexican Sign Language Recognition Using Jacobi-Fourier Moments"
written by Francisco Solís, Carina Toxqui, David Martínez,
published by Engineering, Vol.7 No.10, 2015

has been cited by the following article(s):

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[1]	Spatial–temporal attention with graph and general neural network-based sign language recognition
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[2]	Deriving socio-technical good practices for automatic sign language processing systems from socially aware codesign
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[3]	Hacia la construcción de una base de datos abierta de la LSM
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[4]	Sistema de reconocimiento del Lenguaje de Señas Mexicano basado en una cámara RGB-D y aprendizaje automático
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[5]	Automatic Recognition of Mexican Sign Language Using a Depth Camera and Recurrent Neural Networks
	Peréz, DM Córdova-Esparza, J Terven… - Applied Sciences, 2022

[6]	A Prototype for Mexican Sign Language Recognition and Synthesis in Support of a Primary Care Physician
	Jiménez, HV Ríos-Figueroa… - IEEE …, 2022

[7]	Use of Spherical and Cartesian Features for Learning and Recognition of the Static Mexican Sign Language Alphabet
	Figueroa, AJ Sánchez-García… - Mathematics, 2022

[8]	Facultad de Informática
	2022

[9]	Robust and discriminative image representation: fractional-order Jacobi-Fourier moments
	2021

[10]	Real-Time Mexican Sign Language Interpretation Using CNN and HMM
	… Conference on Artificial …, 2021

[11]	Real-time Mexican Sign Language recognition
	2017

[12]	Interpretación en tiempo real de lengua de senas mexicana con CNN y HMM

[1]	Sign Language Recognition Using Graph and General Deep Neural Network Based on Large Scale Dataset IEEE Access, 2024 DOI:10.1109/ACCESS.2024.3372425

[2]	Spatial–temporal attention with graph and general neural network-based sign language recognition Pattern Analysis and Applications, 2024 DOI:10.1007/s10044-024-01229-4

[3]	Advanced Hybrid Neural Networks for Accurate Recognition of the Extended Alphabet and Dynamic Signs in Mexican Sign Language (MSL) Applied Sciences, 2024 DOI:10.3390/app142210186

[4]	Inteligencia artificial transformación, retos y prospectiva social 2024 DOI:10.61728/AE24001113

[5]	Automatic Recognition of Mexican Sign Language Using a Depth Camera and Recurrent Neural Networks Applied Sciences, 2022 DOI:10.3390/app12115523

[6]	Use of Spherical and Cartesian Features for Learning and Recognition of the Static Mexican Sign Language Alphabet Mathematics, 2022 DOI:10.3390/math10162904

[7]	Automatic Recognition of Mexican Sign Language Using a Depth Camera and Recurrent Neural Networks Applied Sciences, 2022 DOI:10.3390/app12115523

[8]	Use of Spherical and Cartesian Features for Learning and Recognition of the Static Mexican Sign Language Alphabet Mathematics, 2022 DOI:10.3390/math10162904

[9]	A Prototype for Mexican Sign Language Recognition and Synthesis in Support of a Primary Care Physician IEEE Access, 2022 DOI:10.1109/ACCESS.2022.3226696

[10]	A Prototype for Mexican Sign Language Recognition and Synthesis in Support of a Primary Care Physician IEEE Access, 2022 DOI:10.1109/ACCESS.2022.3226696

[11]	Advances in Computational Intelligence Lecture Notes in Computer Science, 2021 DOI:10.1007/978-3-030-89817-5_4

[12]	Advances in Computational Intelligence Lecture Notes in Computer Science, 2021 DOI:10.1007/978-3-030-89817-5_4

[13]	Real-time Mexican Sign Language recognition 2017 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), 2017 DOI:10.1109/ROPEC.2017.8261606

[14]	Automatic Mexican Sign Language Recognition Using Normalized Moments and Artificial Neural Networks Engineering, 2016 DOI:10.4236/eng.2016.810066

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