Analysis of Depth and Semantic Mask for Perceiving a Physical Environment Using Virtual Samples Generated by a GAN-Reference-Cited by-同舟云学术

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Analysis of Depth and Semantic Mask for Perceiving a Physical Environment Using Virtual Samples Generated by a GAN

Published:2022 Issue: Volume:10 Page:5595-5607
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Maldonado-Romo Javier^ORCID,Aldape-Perez Mario^ORCID,Rodriguez-Molina Alejandro^ORCID

Funder

Secretaría de Investigación y Posgrado

Comisión de Operación y Fomento de Actividades Académicas (COFAA) of the Instituto Politécnico Nacional

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09661297.pdf?arnumber=9661297

Cited by 3 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. Sample Generation Method Based on Variational Modal Decomposition and Generative Adversarial Network (VMD–GAN) for Chemical Oxygen Demand (COD) Detection Using Ultraviolet Visible Spectroscopy;Applied Spectroscopy;2023-07-27

2. Path Generator with Unpaired Samples Employing Generative Adversarial Networks;Sensors;2022-12-02

3. A Comprehensive Review on Artificial Intelligence/Machine Learning Algorithms for Empowering the Future IoT Toward 6G Era;IEEE Access;2022

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