Inclusive Consistency-Based Quantitative Decision-Making Framework for Incremental Automatic Target Recognition-Reference-Cited by-同舟云学术

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Inclusive Consistency-Based Quantitative Decision-Making Framework for Incremental Automatic Target Recognition

Published:2023 Issue: Volume:61 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Dang Sihang¹^ORCID,Xia Zhaoqiang²^ORCID,Jiang Xiaoyue²,Gui Shuliang³^ORCID,Feng Xiaoyi²^ORCID

Affiliation:

1. Collaborative Innovation Center of NPU and the School of Electronics and Information, Northwestern Polytechnical University, Shanghai, China

2. School of Electronics and Information, Northwestern Polytechnical University, Xi’an, China

3. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China

Funder

National Natural Science Foundation of China

Shanghai Sailing Program

QINCHUANGYUAN Program

Engineering Research Center of Mobile Communications, Ministry of Education

Key Research and Development Program of Shaanxi

International Science and Technology Cooperation Research Project of Shenzhen

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10239453.pdf?arnumber=10239453

Reference65 articles.

1. The Extreme Value Machine

2. Adaptive Convolutional Subspace Reasoning Network for Few-Shot SAR Target Recognition

3. Distribution Reliability Assessment-Based Incremental Learning for Automatic Target Recognition

4. Support vector machines for SAR automatic target recognition

5. Collective Decision for Open Set Recognition

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