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Deep-Learning-Empowered 3D Reconstruction for Dehazed Images in IoTEnhanced Smart Cities

Jing Zhang1,2, Xin Qi3,*, San Hlaing Myint3, Zheng Wen4

1 Department of Computer Science and Technology, Xi’an University of Science and Technology, Xi’an, 710054, China
2 Tamoritsusho Co., Ltd., Tokyo, 110-0005, Japan
3 Global Information and Telecommunication Institute, Waseda University, Tokyo, 169-8050, Japan
4 School of Fundamental Science and Engineering, Waseda University, Tokyo, 169-8050, Japan

* Corresponding Author: Xin Qi. Email: email

Computers, Materials & Continua 2021, 69(2), 2809-2809. https://doi.org/10.32604/cmc.2021.17410

Abstract

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APA Style
Zhang, J., Qi, X., Myint, S.H., Wen, Z. (2021). Deep-learning-empowered 3D reconstruction for dehazed images in iotenhanced smart cities. Computers, Materials & Continua, 69(2), 2809-2809. https://doi.org/10.32604/cmc.2021.17410
Vancouver Style
Zhang J, Qi X, Myint SH, Wen Z. Deep-learning-empowered 3D reconstruction for dehazed images in iotenhanced smart cities. Comput Mater Contin. 2021;69(2):2809-2809 https://doi.org/10.32604/cmc.2021.17410
IEEE Style
J. Zhang, X. Qi, S.H. Myint, and Z. Wen "Deep-Learning-Empowered 3D Reconstruction for Dehazed Images in IoTEnhanced Smart Cities," Comput. Mater. Contin., vol. 69, no. 2, pp. 2809-2809. 2021. https://doi.org/10.32604/cmc.2021.17410



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