Multi-Class Crevasse Detection Using Ground Penetrating Radar and Feature-Based Machine Learning-Reference-Cited by-同舟云学术

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Multi-Class Crevasse Detection Using Ground Penetrating Radar and Feature-Based Machine Learning

Published:2019-07 Issue: Volume: Page:
ISSN:
Container-title:IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Walker Benjamin,Ray Laura

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8891871/8897702/08899148.pdf?arnumber=8899148

Cited by 8 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. Multi-label classification with deep learning techniques applied to the B-Scan images of GPR;Comptes Rendus. Physique;2024-09-05

2. Classification Size of Underground Object from Ground Penetrating Radar Image using Machine Learning Technique;Journal of Physics: Conference Series;2023-08-01

3. Microwave Synthetic Aperture Radar based Imaging Technique for Crevasse Identification in Glacier Terrain;2022 IEEE Microwaves, Antennas, and Propagation Conference (MAPCON);2022-12-12

4. Gabor-based U-Net crevasse detection with ground penetrating radar data;19th International Conference on Ground Penetrating Radar;2022-10-13

5. Application of Machine Leaning Methods in Geoscience;2022 IEEE 2nd International Conference on Electronic Technology, Communication and Information (ICETCI);2022-05-27

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