Comparative Study Between Deep Learning Techniques and Random Forest Approach for HRRP Based Radar Target Classification-Reference-Cited by-同舟云学术

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Comparative Study Between Deep Learning Techniques and Random Forest Approach for HRRP Based Radar Target Classification

Published:2021-03-25 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS)
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Author:

Sagayaraj M. Justin,Jithesh V.,Roshani Dange

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9395728/9395748/09395855.pdf?arnumber=9395855

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-Driven Back Projection for Target Scattering Modeling VIA Radar Sensor Network;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

2. Artificial Intelligence applications in Noise Radar Technology;IET Radar, Sonar & Navigation;2024-06-28

3. High-Resolution Range Profile Target Recognition with Neuromorphic ADCs and Spiking Neural Networks;2024 IEEE Radar Conference (RadarConf24);2024-05-06

4. Integrating Smart Technologies for Enhanced Traffic Management and Road Safety: A Data-Driven Approach;2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS);2023-08-23

5. Software Development Simulation Model of the Radar Environment with Verification Based on Full-Scale Experiment;2023 Radiation and Scattering of Electromagnetic Waves (RSEMW);2023-06-26

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