A Binary Grey Wolf Optimization based Hybrid Convolutional Neural Network (BGWOHCNN) framework for hyperspectral image classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-15529-0.pdf
Reference66 articles.
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2. Chen Y, Jiang H, Li C, Jia X, Ghamisi P (2016) Deep feature extraction and classification of hyperspectral images based on convolutional neural networks. IEEE Trans Geosci Remote Sens 54(10):6232–6251
3. Chen C, Jiang F, Yang C, Rho S, Shen W, Liu S, Liu Z (2018) Hyperspectral classification based on spectral–spatial convolutional neural networks. Eng Appl Artif Intell 68:165–171
4. Chen Y, Zhu K, Zhu L, He X, Ghamisi P, Benediktsson J A (2019) Automatic design of convolutional neural network for hyperspectral image classification. IEEE Trans Geosci Remote Sens 57(9):7048–7066
5. Cheng J, Wang P, Li G, Hu Q, Lu H (2018) Recent advances in efficient computation of deep convolutional neural networks. arXiv:1802.00939
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