MICAnet: A Deep Convolutional Neural Network for mineral identification on Martian surface-Reference-Cited by-同舟云学术

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MICAnet: A Deep Convolutional Neural Network for mineral identification on Martian surface

Published:2024-09 Issue:3 Volume:27 Page:501-507
ISSN:1110-9823
Container-title:The Egyptian Journal of Remote Sensing and Space Sciences
language:en
Short-container-title:The Egyptian Journal of Remote Sensing and Space Sciences

Author:

Kumari Priyanka^ORCID,Soor Sampriti,Shetty Amba,Koolagudi Shashidhar G.

Publisher

Elsevier BV

Reference20 articles.

1. TensorFlow: Large-scale machine learning on heterogeneous systems;Abadi,2015

2. Automatic, exploratory mineralogical mapping of CRISM imagery using summary product signatures;Allender;Icarus,2017

3. An evaluation of low-rank mahalanobis metric learning techniques for hyperspectral image classification;Bue;IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.,2014

4. Automated processing of planetary hyperspectral datasets for the extraction of weak mineral signatures and applications to CRISM observations of hydrated silicates on mars;Carter;Planet. Space Sci.,2013

5. A review of the F-measure: Its history, properties, criticism, and alternatives;Christen;ACM Comput. Surv.,2023

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