LAND TARGET DETECTION IN REMOTE SENSING IMAGES: METHODS AND APPLICATIONS

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

Land target detection in remote sensing images has become an essential research domain due to its significant role in environmental monitoring, urban development, defense surveillance, and disaster management. The increasing availability of high-resolution satellite imagery demands efficient and accurate detection techniques. This paper presents a comprehensive study of land target detection approaches, including traditional image processing methods and advanced machine learning and deep learning techniques. Modern algorithms such as Convolutional Neural Networks (CNNs), YOLO, and Faster R-CNN have significantly enhanced detection accuracy and speed. The study concludes that integrating artificial intelligence with remote sensing significantly improves detection performance.

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Keywords

Remote sensing, land target detection, deep learning, CNN, YOLO, image processing