Satellite Image Classification using Machine Learning Technique |
Author(s): |
| Dr. Khushbu R. Joshi , LDRP Institute of Technology and Research, Gandhinagar, India |
Keywords: |
| Image Classification, HLAC, Object Detection, Remote Sensing, Satellite Image, SVM |
Abstract |
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Satellites are used to monitor the earth's surface. During the day millions of images are taken by satellites. To analyze a large amount of data manually is a tedious task. An automatic classification technique is required that classifies the images into different classes. Machine learning techniques are extensively used for the classification of satellite images. In this study, we proposed a classification system that classifies the satellite images with high accuracy. In this paper, the features were extracted from the satellite images using the Higher-order Local Auto Correlation method. The EuroSAT dataset was used to train and test the model. The performance of the proposed system was evaluated by accuracy and F1-score. The experimental results showed good and remarkable results. Further, the results were improved by using different SVM kernels. |
Other Details |
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Paper ID: LDRPTCP059 Published in: Conference 12 : LDRP TECON23 Publication Date: 23/12/2023 Page(s): 313-316 |
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