Lightweight GWO-LSTM-Based Land Cover Classification using Remote Sensing Images-Reference-Cited by-同舟云学术

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Lightweight GWO-LSTM-Based Land Cover Classification using Remote Sensing Images

Published:2023-10-20 Issue: Volume: Page:1-5
ISSN:
Container-title:2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT)
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Author:

D Regan¹,Ravindran Gobinath²,Senthil P.³,Rani M. Jamuna⁴,Chakraborty Subhra⁵

Affiliation:

1. Siddartha Institute of Science and Technology,ECE,Puttur,India

2. SR University,Department of Civil Engineering,Warangal,India

3. S.A. Engineering College,Department of Information Technology,Chennai,India

4. Sona College of Technology,Department of ECE,Salem,India

5. Nitte Meenakshi Institute of Technology,Department of ECE,Bengaluru,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10391855/10391862/10393821.pdf?arnumber=10393821

Reference14 articles.

1. Spatial–Spectral Attention Network Guided With Change Magnitude Image for Land Cover Change Detection Using Remote Sensing Images

2. STIP-GCN: Space-time interest points graph convolutional network for action recognition

3. Multi-spectral remote sensing land-cover classification based on deep learning methods

4. Fusion Methods and Multi-classifiers to Improve Land Cover Estimation Using Remote Sensing Analysis

5. Remote sensing inversion and prediction of land use land cover in the middle reaches of the Yangtze River basin, China

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