Enhanced detection of cement plants in remote sensing images using modified faster R-CNN

Tianzhu Li; Caihong Ma; Ruilin Liao; Jianbo Liu; Jin Yang

doi:10.1117/12.3007968

30 August 2023 Enhanced detection of cement plants in remote sensing images using modified faster R-CNN

Tianzhu Li, Caihong Ma, Ruilin Liao, Jianbo Liu, Jin Yang

Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 1279717 (2023) https://doi.org/10.1117/12.3007968
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China

Abstract

Accurate extraction of cement plants is important for the regulation of polluting enterprises and environmental protection. Conventional cement plant identification methods are characterized by low efficiency, high cost, and limitations incomprehensive and precise monitoring. Considering the successful application of deep learning in visual object detection, this research presents a modified Faster R-CNN network tailored specifically for detecting cement plants in remote sensing images. Our approach utilizes a multi-level fusion structure, integrating deep semantic features with more superficial detail features. This combination yields multi-scale feature maps that provide precise positional data along with deep semantic context. The experimental results demonstrate that our proposed method effectively detects multi- scale cement factory targets in remote sensing images, reducing the omission rate and improving target localization accuracy.

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

Citation Download Citation

Tianzhu Li, Caihong Ma, Ruilin Liao, Jianbo Liu, and Jin Yang "Enhanced detection of cement plants in remote sensing images using modified faster R-CNN", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 1279717 (30 August 2023); https://doi.org/10.1117/12.3007968

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KEYWORDS

Object detection

Cements

Remote sensing

Target detection

Education and training

Feature extraction

Data modeling

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