Real-Time Recognition and Tracking in Urban Spaces Through Deep Learning: A Case Study-Reference-Cited by-同舟云学术

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Real-Time Recognition and Tracking in Urban Spaces Through Deep Learning: A Case Study

Published:2024 Issue: Volume:12 Page:95599-95612
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Villegas William Eduardo¹^ORCID,Sánchez-Viteri Santiago²,Luján-Mora Sergio³^ORCID

Affiliation:

1. Escuela de Ingeniería en Ciberseguridad, FICA, Universidad de las Américas, Quito, Ecuador

2. Departamento de Sistemas, Universidad Internacional del Ecuador, Quito, Ecuador

3. Department of Software and Computing Systems, University of Alicante, Alicante, Spain

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10592064.pdf?arnumber=10592064

Reference43 articles.

1. Urban environment and obesity and weight-related behaviours in primary school children

2. Deep learning-based waste detection in natural and urban environments

3. Automated Simulation Framework for Urban Wind Environments Based on Aerial Point Clouds and Deep Learning

4. Phenotyping urban built and natural environments with high-resolution satellite images and unsupervised deep learning

5. Deep learning method for minimizing water pollution and air pollution in urban environment

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