Skeleton-Based Gait Recognition Using Modified Deep Convolutional Neural Networks and Long Short-Term Memory for Person Recognition-Reference-Cited by-同舟云学术

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Skeleton-Based Gait Recognition Using Modified Deep Convolutional Neural Networks and Long Short-Term Memory for Person Recognition

Published:2024 Issue: Volume:12 Page:121131-121143
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Tri Yunardi Riky¹^ORCID,Arief Sardjono Tri¹^ORCID,Mardiyanto Ronny¹^ORCID

Affiliation:

1. Department of Electrical Engineering, Faculty of Intelligent Electrical and Informatics Technology, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

Funder

Ministry of Education, Culture, Research, and Technology, Republic of Indonesia under Penelitian Disertasi Doktor 2023 research grant

Balai Pembiayaan Pendidikan Tinggi (BPPT) through the Lembaga Pengelola Dana Pendidikan (LPDP) under Beasiswa Pendidikan Indonesia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10654784.pdf?arnumber=10654784

Reference31 articles.

1. Prosperous Human Gait Recognition: an end-to-end system based on pre-trained CNN features selection

2. View-Independent Gait Recognition Using Joint Replacement Coordinates (JRCs) and Convolutional Neural Network

3. User Verification Leveraging Gait Recognition for Smartphone Enabled Mobile Healthcare Systems

4. A High-Performance Gait Recognition Method Based on n-Fold Bernoulli Theory

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