Resnet based hybrid convolution LSTM 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/s11042-023-16241-9.pdf
Reference31 articles.
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2. Signoroni A, Savardi M, Baronio A, Benini S (2019) Deep learning meets hyperspectral image analysis: a multidisciplinary review. J Imaging 5(5):52
3. Mou L, Ghamisi P, Zhu XX (2017) Deep recurrent neural networks for hyperspectral image classification. In: IEEE transactions on geoscience and remote sensing, vol 55, no 7, pp 3639–3655. https://doi.org/10.1109/TGRS.2016.2636241
4. He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770–778
5. Amy L, Harrison N, French AP (2017) Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress. Plant methods 13(1):1–12
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