Multispectral Satellite Image Classification Using Hybrid Convolution Neural Network-Reference-Cited by-同舟云学术

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Multispectral Satellite Image Classification Using Hybrid Convolution Neural Network

Published:2021-11-24 Issue: Volume: Page:541-550
ISSN:2194-5357
Container-title:Proceedings of International Conference on Advanced Computing Applications
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Author:

Kundu Krishan,Halder Prasun,Mandal Jyotsna Kumar

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-5207-3_45

Reference14 articles.

1. Zhang, P., Ke, Y., Zhang, Z., Wang, M., Li, P., Zhang, S.: Urban land use and land cover classification using novel deep learning models based on high spatial resolution satellite imagery. Sensors 18(11), 3717 (2018)

2. Kundu, K., Halder, P., Mandal, J.K.: Urban change detection analysis during 1978–2017 at Kolkata, India, using multi-temporal satellite data. J. Indian Soc. Remote Sens. 48, 1535–1554 (2020)

3. Zhu, X.X., Tuia, D., Mou, L., Xia, G.S., Zhang, L., Xu, F., Fraundorfer, F.: Deep learning in remote sensing: a comprehensive review and list of resources. IEEE Geosci. Remote Sens. Mag. 5(4), 8–36 (2017)

4. Kundu, K., Halder, P., Mandal, J.K.: Forest cover change analysis in Sundarban delta using remote sensing data and GIS. In: Intelligent Computing Paradigm: Recent Trends Studies in Computational Intelligence, vol. 784, pp. 85–101. Springer, Singapore (2019)

5. Kundu, K., Halder, P., Mandal, J.K.: Forest covers classification of Sundarban on the basis of fuzzy C-means algorithm using satellite images. In: Mandal, J., Mukhopadhyay, S. (eds.) Proceedings of the Global AI Congress 2019. Advances in Intelligent Systems and Computing, vol. 1112, pp. 515–528 (2020)

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