Citation: | JIN Yaqiu. Multimode remote sensing intelligent information and target recognition: Physical intelligence of microwave vision[J]. Journal of Radars, 2019, 8(6): 710–716. doi: 10.12000/JR19083 |
[1] |
MIT Schwarzman College of Computing. The MIT Stephen A. Schwarzman College of Computing aims to address the global opportunities and challenges presented by the ubiquity of computing — across industries and academic disciplines — perhaps most notably illustrated by the rise of artificial intelligence[EB/OL]. http://computing.mit.edu/about/, 2018.
|
[2] |
L Rafael Reif. Prepare students for a future of artificial intelligence[EB/OL]. https://president.mit.edu/speeches-writing/prepare-students-future-artificial-intelligence/2019-02-10.
|
[3] |
李婕敏. 美国白宫积极布局人工智能未来发展[J]. 现代军事, 2017(S1): 20–21.
LI Jiemin. The White House is actively planning the future development of artificial intelligence[J]. conmilit, 2017(S1): 20–21.
|
[4] |
DARPA announces $2 billion campaign to develop next wave of AI technologies[EB/OL]. https://www.darpa.mil/news-events/2018-09-07.
|
[5] |
2018年国防部人工智能战略概要——利用人工智能促进安全与繁荣[EB/OL]. http://www.defense-aerospace.com/articles-view/reports/2/199929/pentagon-releases-artificial-intelligence-strategy.html, 2019.
Summary of the 2018 Department of Defense Artificial Intelligence Strategy——Harnessing AI to Advance Our Security and Prosperity[EB/OL]. http://www.defense-aerospace.com/articles-view/reports/2/199929/pentagon-releases-artificial-intelligence-strategy.html, 2019.
|
[6] |
AI next campaign[EB/OL]. https://www.darpa.mil/work-with-us/ai-next-campaign.
|
[7] |
Gouvernement. fr. FranceIA: The national artificial intelligence strategy is underway[EB/OL]. https://www.gouvernement.fr/en/franceia-the-national-artificial-intelligence-strategy-is-underway, 2017.
|
[8] |
详解世界各国的人工智能布局[EB/OL]. https://blog.csdn.net/R1uNW1W/article/details/78399834, 2017.
Detailed understanding of the world's AI layout[EB/OL]. https://blog.csdn. net/R1uNW1W/article/details/78399834, 2017.
|
[9] |
JapanGov. Artificial intelligence: a rival for humans, or A Partner?[EB/OL]. https://www.japan.go.jp/tomodachi/2018/spring2018/artificial_intelligence.html, 2018.
|
[10] |
新一代人工智能发展规划[EB/OL]. http://www.gov.cn/xinwen/2017-07/20/content_5212064.htm, 2017.
A new generation of the AI development plan[EB/OL]. http://www.gov.cn/xinwen/2017-07/20/content_5212064.htm, 2017.
|
[11] |
国家自然科学基金人工智能基础研究应急项目指南[EB/OL]. http://www.nsfc.gov.cn/publish/portal0/tab452/info69927.htm.
National natural science foundation’s AI-based basic research emergency project guide[EB/OL]. http://www.nsfc.gov.cn/publish/portal0/tab452/info69927.htm.
|
[12] |
XU Feng and JIN Y. Remote sensing with intelligent processing 2017 in Shanghai, China[J]. IEEE Geoscience and Remote Sensing Magazine, 2017, 5(4): 108–123. doi: 10.1109/MGRS.2017.2760619
|
[13] |
ZHOU Yu, WANG Haipeng, XU Feng, et al. Polarimetric SAR image classification using deep convolutional neural networks[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(12): 1935–1939. doi: 10.1109/LGRS.2016.2618840
|
[14] |
SONG Qian and XU Feng. Zero-shot learning of SAR target feature space with deep generative neural networks[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(12): 2245–2249. doi: 10.1109/LGRS.2017.2758900
|
[15] |
CHEN Sizhe, WANG Haipeng, XU Feng, et al. Target classification using the deep convolutional networks for SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(8): 4806–4817. doi: 10.1109/TGRS.2016.2551720
|
[16] |
ZHANG Zhimian, WANG Haipeng, XU Feng, et al. Complex-valued convolutional neural network and its application in Polarimetric SAR image classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(12): 7177–7188. doi: 10.1109/TGRS.2017.2743222
|
[17] |
徐丰, 金亚秋. 从物理智能到微波视觉[J]. 科技导报, 2018, 36(10): 30–44. doi: 10.3981/j.issn.1000-7857.2018.10.004
XU Feng and JIN Yaqiu. From the emergence of intelligent science to the research of microwave vision[J]. Science&Technology Review, 2018, 36(10): 30–44. doi: 10.3981/j.issn.1000-7857.2018.10.004
|
[18] |
金亚秋, 徐丰. 加强智能科学交叉领域研究[J]. 科技导报, 2018, 36(17): 1.
JIN Yaqiu and XU Feng. To strengthen the research on the intersection of intelligence science[J]. Science&Technology Review, 2018, 36(17): 1.
|
[19] |
金亚秋, 徐丰. 极化散射与SAR遥感信息理论与方法[M]. 北京: 科学出版社, 2008.
JIN Yaqiu and XU Feng. Theory and Approach for Polarimetric Scattering and Information Retrieval of SAR Remote Sensing[M]. Beijing: Science Press, 2008.
|
[20] |
姜景山, 吴一戎, 金亚秋. 空间微波遥感研究与应用丛书[M]. 北京: 科学出版社, 2019–2020.
JIANG Jingshan, WU Yirong, and JIN Yaqiu. Book Series on Space-Borne Microwave Remote Sensing[M]. Beijing: Science Press, 2019–2020.
|
[21] |
徐丰, 王海鹏, 金亚秋. 雷达图像智能信息解译与应用[M]. 北京: 科学出版社, 2020.
XU Feng, WANG Haipeng, and JIN Yaqiu. Intelligent Interpretation of Radar Image Information[M]. Beijing: Science Press, 2020.
|
[22] |
徐丰, 王海鹏, 金亚秋. 深度学习在SAR目标识别与地物分类中的应用[J]. 雷达学报, 2017, 6(2): 136–148. doi: 10.12000/JR16130
XU Feng, WANG Haipeng, and JIN Yaqiu. Deep learning as applied in SAR Target recognition and terrain classification[J]. Journal of Radars, 2017, 6(2): 136–148. doi: 10.12000/JR16130
|
[23] |
YUE Dongxiao, XU Feng, and JIN Yaqiu. SAR despeckling neural network with logarithmic convolutional product model[J]. International Journal of Remote Sensing, 2018, 39(21): 7483–7505. doi: 10.1080/01431161.2018.1471539
|
[24] |
SONG Qian, XU Feng, and JIN Yaqiu. Radar image colorization: Converting single-polarization to fully polarimetric using deep neural networks[J]. IEEE Access, 2017, 6: 1647–1661.
|