Prediction of multi-layer metasurface design using conditional deep convolutional generative adversarial networks

被引：0
|
作者：
Nezaratizadeh, Ali [1 ]
Hashemi, Seyed Mohammad [2 ]
Bod, Mohammad [2 ]
机构：
[1] Department of Electrical and Computer Engineering, University of Florida, Gainesville,FL, United States
[2] Department of Electrical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
来源：
Optik | 2024年 / 313卷
关键词：
Compendex;
D O I：
10.1016/j.ijleo.2024.172005
中图分类号：
学科分类号：
摘要：
Generative adversarial networks
引用
收藏
相关论文
共 50 条
  • [21] Deep convolutional generative adversarial networks assisted inverse design of quad-channel full-space metasurface
    Liu, Xiaosong
    Cao, Xianbo
    Hong, Tao
    Jiang, Wen
    OPTICS EXPRESS, 2024, 32 (26): : 46542 - 46556
  • [22] Metamodeling of a deep drawing process using conditional Generative Adversarial Networks
    Link, Patrick
    Bodenstab, Johannes
    Penter, Lars
    Ihlenfeldt, Steffen
    INTERNATIONAL DEEP-DRAWING RESEARCH GROUP CONFERENCE (IDDRG 2022), 2022, 1238
  • [23] Comparative Analysis of Deep Convolutional Generative Adversarial Network and Conditional Generative Adversarial Network using Hand Written Digits
    Prabhat
    Nishant
    Vishwakarma, Dinesh Kumar
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS 2020), 2020, : 1072 - 1075
  • [24] Traffic Prediction in Optical Networks Using Graph Convolutional Generative Adversarial Networks
    Vinchoff, C.
    Chung, N.
    Gordon, T.
    Lyford, L.
    Aibin, M.
    2020 22ND INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS (ICTON 2020), 2020,
  • [25] Multi-Phase Offline Signature Verification System Using Deep Convolutional Generative Adversarial Networks
    Zhang, Zehua
    Liu, Xiangqian
    Cui, Yan
    PROCEEDINGS OF 2016 9TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 2, 2016, : 103 - 107
  • [26] Quick Prediction of Complex Temperature Fields Using Conditional Generative Adversarial Networks
    Wu, Xiaohua
    Lu, Longsheng
    Liang, Lanzhi
    Mei, Xiaokang
    Liang, Qinghua
    Zhong, Yilin
    Huang, Zeqiang
    Yang, Shu
    He, Hengfei
    Xie, Yingxi
    ASME JOURNAL OF HEAT AND MASS TRANSFER, 2024, 146 (11):
  • [27] Prediction for underground seismic intensity measures using conditional generative adversarial networks
    Duan, Shuqian
    Song, Zebin
    Shen, Jiaxu
    Xiong, Jiecheng
    SOIL DYNAMICS AND EARTHQUAKE ENGINEERING, 2024, 180
  • [28] Inverse design of electromagnetically induced transparency(EIT) metasurface based on deep convolutional generative adversarial network
    Zhu, Lei
    Zhang, Cong
    Dong, Liang
    Rong, Miao Xin
    Gong, Jin Yue
    Meng, Fan-Yi
    PHYSICA SCRIPTA, 2023, 98 (10)
  • [29] Font Creation Using Class Discriminative Deep Convolutional Generative Adversarial Networks
    Abe, Kotaro
    Iwana, Brian Kenji
    Holmer, Viktor Gosta
    Uchida, Seiichi
    PROCEEDINGS 2017 4TH IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION (ACPR), 2017, : 232 - 237
  • [30] Anomaly detection using deep convolutional generative adversarial networks in the internet of things
    Mishra, Amit Kumar
    Paliwal, Shweta
    Srivastava, Gautam
    ISA TRANSACTIONS, 2024, 145 : 493 - 504
12345