Shuai, Yuanzhen, Xin, Ning, Hasan, Md Maruf, Hu, Bintao, Dai, Tianhong and Liu, Hengyan
(2023)
Application of IMVR Convolutional Neural Networks to Classification of Land Use Remote Sensing Datasets.
In: 2023 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2023-11-2 - 2023-11-4.
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Abstract
Despite extensive research, remote sensing image classification remains a challenging issue within the field of remote sensing image analysis. Achieving a balance between classification accuracy and computational efficiency remains challenging, as traditional methods often face difficulties in attaining both high speed and precision simultaneously. To tackle this dilemma, we propose a method named IMVR which significantly reduces the computational burden while maintaining validity. This method enhances the richness and accuracy of high-dimensional feature representations through its output. Extensive experiments are conducted on the UC Merced Land-Use Dataset to demonstrate that our method can substantially improve classification performance and efficiency in comparison to traditional methods.
| Item Type: | Conference or Workshop Item (Unspecified) |
|---|---|
| Uncontrolled Keywords: | 15 Life on Land, 14 Life Below Water |
| Divisions: | Faculty of Science and Engineering > School of Physical Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 27 Mar 2024 15:09 |
| Last Modified: | 27 Mar 2024 15:09 |
| DOI: | 10.1109/cyberc58899.2023.00015 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3179857 |
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