Predicting Classification Performance for Benchmark Hyperspectral Datasets
Author:
Affiliation:
1. Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland
2. Jülich Supercomputing Centre, Jülich, Germany
Funder
Research Fund of the University of Iceland
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Atmospheric Science,Computers in Earth Sciences
Link
http://xplorestaging.ieee.org/ielx7/4609443/9656571/09772265.pdf?arnumber=9772265
Reference117 articles.
1. Parallel Morphological Classification of Hyperspectral Imagery Using Extended Opening and Closing by Reconstruction Operations
2. Impact of different morphological profiles on the classification accuracy of urban hyperspectral data
3. Multiple Morphological Profiles From Multicomponent-Base Images for Hyperspectral Image Classification
4. Ensemble classification of hyperspectral images based on ordered weighted averaging operators
5. Decision fusion based on extended multi-attribute profiles for hyperspectral image classification
Cited by 1 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. Spectral–Spatial Features Exploitation Using Lightweight HResNeXt Model for Hyperspectral Image Classification;Canadian Journal of Remote Sensing;2023-07-12
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