Fast and Efficient Limited Data Hyperspectral Remote Sensing Image Classification via GMM-Based Synthetic Samples
Author:
Funder
German Academic Exchange Service
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Atmospheric Science,Computers in Earth Sciences
Link
http://xplorestaging.ieee.org/ielx7/4609443/8789745/08734704.pdf?arnumber=8734704
Cited by 10 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. A joint method of spatial–spectral features and BP neural network for hyperspectral image classification;The Egyptian Journal of Remote Sensing and Space Science;2023-02
2. Bayesian Convolutional Neural Networks for Limited Data Hyperspectral Remote Sensing Image Classification;IEEE Geoscience and Remote Sensing Letters;2023
3. Distributed Cloud Computing Architecture in Hyperspectral Remote Sensing Image Classification under Big Data;2022 IEEE 5th International Conference on Information Systems and Computer Aided Education (ICISCAE);2022-09-23
4. Band Selection Technique for Crop Classification Using Hyperspectral Data;Journal of the Indian Society of Remote Sensing;2022-04-21
5. On Mathews Correlation Coefficient and Improved Distance Map Loss for Automatic Glacier Calving Front Segmentation in SAR Imagery;IEEE Transactions on Geoscience and Remote Sensing;2022
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