Enhanced classification of remotely sensed hyperspectral images through efficient band selection using autoencoders and genetic algorithm
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-021-06121-4.pdf
Reference64 articles.
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3. Bhattacharya S, Das S, Routray A (2018) Graph manifold clustering based band selection for hyperspectral face recognition. In: 2018 26th European signal processing conference (EUSIPCO). IEEE, pp 1990–1994
4. Borengasser M, Hungate WS, Watkins R (2007) Hyperspectral remote sensing: principles and applications. In: Remote sensing applications series. CRC Press
5. Burges CJ (1998) A tutorial on support vector machines for pattern recognition. Data Min Knowl Discov 2:121–167
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