A COMPLEX-VALUED CONVOLUTIONAL NEURAL NETWORK WITH DIFFERENT ACTIVATION FUNCTIONS IN POLARIMETRIC SAR IMAGE CLASSIFICATION

被引：3
|
作者：
Zhang, Yun [1 ]
Hua, Qinglong [1 ]
Xu, Dan [1 ]
Li, Hongbo [1 ]
Mu, HuiLin [1 ]
机构：
[1] Harbin Inst Technol, Sch Elect Informat Engn, Harbin, Peoples R China
来源：
2019 INTERNATIONAL RADAR CONFERENCE (RADAR2019) | 2019年
基金：
中国国家自然科学基金;
关键词：
Complex-valued convolutional neural network (CV-CNN); optimization algorithm; activation function; synthetic aperture radar (SAR); terrain classification; deep learning;
D O I：
10.1109/RADAR41533.2019.171298
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
It is well known that the activation function and the gradient descent optimization algorithm have a great influence on convolutional neural network (CNN). Based on the Adam optimization algorithm, this paper proposes a CvAdam optimization algorithm suitable for complex-valued convolutional neural network (CV-CNN), and then in the typical polarization SAR image classification task, Adam and CvAdam were compared using four different activation functions of sigmoid, tanh, Leakey-ReLU and ELU. Experiments on the benchmark dataset of Oberpfaffenhofen show that CvAdam performs better than Adam in both convergence speed and accuracy, no matter which activation function is used.
引用
收藏
页码：749 / 752
页数：4
相关论文
共 50 条
  • [1] Complex-Valued Convolutional Neural Network and Its Application in Polarimetric SAR Image Classification
    Zhang, Zhimian
    Wang, Haipeng
    Xu, Feng
    Jin, Ya-Qiu
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2017, 55 (12): : 7177 - 7188
  • [2] Complex-Valued Full Convolutional Neural Network for SAR Target Classification
    Yu, Lingjuan
    Hu, Yuehong
    Xie, Xiaochun
    Lin, Yun
    Hong, Wen
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2020, 17 (10) : 1752 - 1756
  • [3] A COMPLEX-VALUED CNN FOR DIFFERENT ACTIVATION FUNCTIONS IN POLARSAR IMAGE CLASSIFICATION
    Zhang, Yun
    Hua, Qinglong
    Xu, Dan
    Li, Hongbo
    Bu, Yan
    Zhao, Pengfei
    2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 10023 - 10026
  • [4] A New Architecture of a Complex-Valued Convolutional Neural Network for PolSAR Image Classification
    Ren, Yihui
    Jiang, Wen
    Liu, Ying
    REMOTE SENSING, 2023, 15 (19)
  • [5] Complex-Valued Convolutional Autoencoder and Spatial Pixel-Squares Refinement for Polarimetric SAR Image Classification
    Shang, Ronghua
    Wang, Guangguang
    Okoth, Michael A.
    Jiao, Licheng
    REMOTE SENSING, 2019, 11 (05)
  • [6] SEMI-SUPERVISED COMPLEX-VALUED GAN FOR POLARIMETRIC SAR IMAGE CLASSIFICATION
    Sun, Qigong
    Li, Xiufang
    Li, Lingling
    Liu, Xu
    Liu, Fang
    Jiao, Licheng
    2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 3245 - 3248
  • [7] Complex-Valued 3-D Convolutional Neural Network for PolSAR Image Classification
    Tan, Xiaofeng
    Li, Ming
    Zhang, Peng
    Wu, Yan
    Song, Wanying
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2020, 17 (06) : 1022 - 1026
  • [8] Complex-Valued Convolutional Neural Networks for Real-Valued Image Classification
    Popa, Calin-Adrian
    2017 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2017, : 816 - 822
  • [9] REAL- AND COMPLEX-VALUED NEURAL NETWORKS FOR SAR IMAGE SEGMENTATION THROUGH DIFFERENT POLARIMETRIC REPRESENTATIONS
    Barrachina, J. A.
    Ren, C.
    Vieillard, G.
    Morisseau, C.
    Ovarlez, J. -P.
    2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP, 2022, : 1456 - 1460
  • [10] Despeckling Polarimetric SAR Data Using a Multistream Complex-Valued Fully Convolutional Network
    Mullissa, Adugna G.
    Persello, Claudio
    Reiche, Johannes
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
12345