Improved faster R-CNN algorithm for object detection in remote sensing image

Lizhao Liu; Honghui Yi

doi:10.1117/12.3007960

14 November 2023 Improved faster R-CNN algorithm for object detection in remote sensing image

Lizhao Liu, Honghui Yi

Proceedings Volume 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023); 1293416 (2023) https://doi.org/10.1117/12.3007960
Event: 2023 3rd International Conference on Computer Graphics, Image and Virtualization (ICCGIV 2023), 2023, Nanjing, China

Abstract

To enhance the precision of detecting small targets in remote sensing images, a target detection algorithm based on improved faster R-CNN is proposed in this paper. In order to enhance the ability of feature extraction for image object category, the algorithm uses the large network model EfficientNet in the backbone feature extraction network. introduce an improved FPN (feature pyramid network) model to reduce that loss of key information of small target caused by the deep neural network, enhancing the capability of extracting feature information of the small target of the fast R-CNN model to the remote sensing image, and being capable of better coping with the remote sensing image with complex background and drastic size change, thereby reducing the omission rate. Finally, CBAM attention module is introduced into the feature graph output of the network model to enhance the interest of the model in feature information and improve the detection ability. Experiments on the NWPU_VHR-10 dataset show that the proposed algorithm improves the accuracy by 8.82%.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lizhao Liu and Honghui Yi "Improved faster R-CNN algorithm for object detection in remote sensing image", Proc. SPIE 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023), 1293416 (14 November 2023); https://doi.org/10.1117/12.3007960

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KEYWORDS

Remote sensing

Target detection

Object detection

Image enhancement

Feature extraction

Detection and tracking algorithms

Small targets

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