Mineral classification on Martian surface using CRISM hyperspectral data: a survey-Reference-Cited by-同舟云学术

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Mineral classification on Martian surface using CRISM hyperspectral data: a survey

Published:2023-11-11 Issue:04 Volume:17 Page:
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:
Short-container-title:J. Appl. Rem. Sens.

Author:

Kumari Priyanka¹,Soor Sampriti²,Shetty Amba¹,Koolagudi Shashidhar G.³

Affiliation:

1. National Institute of Technology Karnataka, Department of Water Resources and Ocean Engineering, Mangalore, Karnataka, India

2. Kalinga Institute of Industrial Technology, School of Computer Engineering, Bhubaneswar, Odisha, India

3. National Institute of Technology Karnataka, Department of Computer Science and Engineering, Mangalore, Karnataka, India

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Earth and Planetary Sciences

Cited by 3 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. MICAnet: A Deep Convolutional Neural Network for mineral identification on Martian surface;The Egyptian Journal of Remote Sensing and Space Sciences;2024-09

2. Enhancing Martian Mineral Identification Using an Artificial Neural Network With Extracted Spectral Features In CRISM MTRDR Data;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

3. Weighted Sum of Segmented Correlation: an Efficient Method for Spectra Matching in Hyperspectral Images;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

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