Abstract
Abstract: The classification of images can be influenced by various factors. When multiple sources of data are available for earth exploration, extracting valuable information or achieving effective outcomes can be both fascinating and challenging. Remote Sensing Images (RSI) classification plays a crucial role in remote sensing applications and serves as the foundation for efficient classification. Various classifiers are employed to classify different types of targets in remote sensing images. Achieving improved target classification is of utmost importance in both military and civilian domains. This paper focuses on summarizing advanced approaches used to enhance classification accuracy. The findings indicate that the Convolutional Neural Network surpasses all other conventional classification methods.
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