Training sample selection for space–time adaptive processing based on multi-frames

Chenxiao Zhang; Yifeng Wu; Mingming Guo; Xiaobo Deng

doi:10.1049/joe.2019.0410

Training sample selection for space–time adaptive processing based on multi-frames

The Journal of Engineering ◽

10.1049/joe.2019.0410 ◽

2019 ◽

Vol 2019 (20) ◽

pp. 6369-6372

Author(s):

Chenxiao Zhang ◽

Yifeng Wu ◽

Mingming Guo ◽

Xiaobo Deng

Keyword(s):

Sample Selection ◽

Training Sample ◽

Space Time ◽

Adaptive Processing ◽

Selection For ◽

Space Time Adaptive Processing ◽

Training Sample Selection

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Training Sample Selection for Space-Time Adaptive Processing in Heterogeneous Environments

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2014.2357804 ◽

2015 ◽

Vol 12 (4) ◽

pp. 691-695 ◽

Cited By ~ 23

Author(s):

Yifeng Wu ◽

Tong Wang ◽

Jianxin Wu ◽

Jia Duan

Keyword(s):

Sample Selection ◽

Training Sample ◽

Space Time ◽

Heterogeneous Environments ◽

Adaptive Processing ◽

Selection For ◽

Space Time Adaptive Processing ◽

Training Sample Selection

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A novel heterogeneous training sample selection method on space-time adaptive processing

10.1063/1.5033812 ◽

2018 ◽

Author(s):

Qiang Wang ◽

Yongshun Zhang ◽

Yiduo Guo

Keyword(s):

Sample Selection ◽

Training Sample ◽

Selection Method ◽

Space Time ◽

Adaptive Processing ◽

Space Time Adaptive Processing ◽

Training Sample Selection

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An algorithm of training sample selection for integrated circuit device modeling based on artificial neural networks

2016 IEEE International Conference on Electron Devices and Solid-State Circuits (EDSSC) ◽

10.1109/edssc.2016.7785271 ◽

2016 ◽

Author(s):

Zhiyuan Zhang ◽

Xiaole Cui ◽

Xinnan Lin ◽

Lining Zhang

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Integrated Circuit ◽

Sample Selection ◽

Training Sample ◽

Device Modeling ◽

Selection For ◽

Artificial Neural ◽

Training Sample Selection

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THE QUICK METHOD OF TRAINING SAMPLE SELECTION FOR NEURAL NETWORK DECISION MAKING MODEL BUILDING ON PRECEDENTS

Radio Electronics Computer Science Control ◽

10.15588/1607-3274-2015-1-6 ◽

2015 ◽

Vol 0 (1) ◽

Author(s):

S. A. Subbotin

Keyword(s):

Neural Network ◽

Decision Making ◽

Model Building ◽

Sample Selection ◽

Training Sample ◽

Quick Method ◽

Selection For ◽

Decision Making Model ◽

Training Sample Selection

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An Intelligent Sample Selection Method for Space-Time Adaptive Processing in Heterogeneous Environment

IEEE Access ◽

10.1109/access.2019.2902218 ◽

2019 ◽

Vol 7 ◽

pp. 30321-30330 ◽

Cited By ~ 1

Author(s):

Chongdi Duan ◽

Yu Li ◽

Wei Wei Wang

Keyword(s):

Sample Selection ◽

Selection Method ◽

Space Time ◽

Adaptive Processing ◽

Heterogeneous Environment ◽

Space Time Adaptive Processing

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Training sample selection for deep learning of distributed data

2017 IEEE International Conference on Image Processing (ICIP) ◽

10.1109/icip.2017.8296670 ◽

2017 ◽

Cited By ~ 1

Author(s):

Zheng Jiang ◽

Xiaoqing Zhu ◽

Wai-tian Tan ◽

Rob Liston

Keyword(s):

Deep Learning ◽

Sample Selection ◽

Training Sample ◽

Distributed Data ◽

Selection For ◽

Training Sample Selection

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A graded proportion method of training sample selection for updating conventional soil maps

Geoderma ◽

10.1016/j.geoderma.2019.113939 ◽

2020 ◽

Vol 357 ◽

pp. 113939 ◽

Cited By ~ 3

Author(s):

Xueqi Liu ◽

A-Xing Zhu ◽

Lin Yang ◽

Tao Pei ◽

Junzhi Liu ◽

...

Keyword(s):

Sample Selection ◽

Training Sample ◽

Soil Maps ◽

Proportion Method ◽

Selection For ◽

Training Sample Selection

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Iterative Random Training Sample Selection for Hyperspectral Image Classification

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2019.8898826 ◽

2019 ◽

Cited By ~ 1

Author(s):

Chia-Chen Liang ◽

Yi-Mei Kuo ◽

Kenneth Yeonkong Ma ◽

Peter F. Hu ◽

Chein-I Chang

Keyword(s):

Image Classification ◽

Hyperspectral Image ◽

Sample Selection ◽

Training Sample ◽

Hyperspectral Image Classification ◽

Selection For ◽

Training Sample Selection

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A robust refined training sample reweighting space–time adaptive processing method for airborne radar in heterogeneous environment

IET Radar Sonar & Navigation ◽

10.1049/rsn2.12034 ◽

2021 ◽

Vol 15 (3) ◽

pp. 310-322

Author(s):

Hao Xiao ◽

Tong Wang ◽

Shuguang Zhang ◽

Cai Wen

Keyword(s):

Training Sample ◽

Space Time ◽

Processing Method ◽

Airborne Radar ◽

Adaptive Processing ◽

Heterogeneous Environment ◽

Space Time Adaptive Processing

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On Training Sample Selection for Artificial Neural Networks using Number-Theoretic Methods

Proceedings of the Fourth International Conference on Engineering Computational Technology ◽

10.4203/ccp.80.131 ◽

2009 ◽

Author(s):

F. Tong ◽

X.L. Liu

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Sample Selection ◽

Training Sample ◽

Selection For ◽

Artificial Neural ◽

Training Sample Selection

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