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Academic Journal of Computing & Information Science, 2023, 6(7); doi: 10.25236/AJCIS.2023.060717.

Research on remote sensing image object detection based on convolutional neural network


Meiyan Li1,2, Joey S. Aviles1

Corresponding Author:
Joey S. Aviles

1Graduate School, Angeles University Foundation, Angeles City 2009, Philippines

2School of Information Engineering, Baise University, Baise, 533000, China


With the update of remote sensing equipment and the improvement of technology, remote sensing images not only have advantages in quantity, but also improve in imaging quality. Convolutional neural network has been widely used in object detection, which can extract targets from a large number of images and has a very powerful feature extraction capability. The detection technology for remote sensing images has a promoting role. This paper introduces the application of remote sensing image, analyzes several common convolutional neural network technologies and features, and analyzes the application of convolutional neural network in remote sensing images. Through comparative analysis, the efficiency of convolutional neural network technology is relatively high in remote sensing image target detection, which indeed solves the problems of low detection accuracy and high miss detection rate of remote sensing targets, remote sensing target characteristics and mainstream algorithms in current remote sensing images.


Remote sensing image, Feature ability, convolutional neural network, Object detection

Cite This Paper

Meiyan Li, Joey S. Aviles. Research on remote sensing image object detection based on convolutional neural network. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 7: 131-137. https://doi.org/10.25236/AJCIS.2023.060717.


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