Research on Remote Sensing Image Object Detection 
Algorithm Based on Deep Learning

Kuijie Shi

doi:10.70711/aitr.v2i7.5973

Research on Remote Sensing Image Object Detection Algorithm Based on Deep Learning

Kuijie Shi

Abstract

Remote sensing image object detection, as a key technology to automatically identify and locate objects from a large number of images obtained from space remote sensing equipment (such as satellites and drones), has made significant progress thanks to the development
of deep learning in recent years. Traditional methods have limitations in dealing with complex background, multi-scale target and small target
detection, while the deep learning method represented by convolutional neural network (CNN) significantly improves the detection accuracy
and adaptability through end-to-end training. This paper discusses the research progress and application scenarios of cutting-edge methods
such as feature fusion technology, lightweight network, Transformer model, and semi-supervised and self-supervised learning.

Keywords

Remote sensing image; Object detection; Deep learning; Feature fusion; Lightweight network; Semi-supervised learning

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DOI: http://dx.doi.org/10.70711/aitr.v2i7.5973

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