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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Analysis of the Influence of De-hazing Methods on Vehicle Detection in Aerial Images

Author 1: Khang Nguyen
Author 2: Phuc Nguyen
Author 3: Doanh C. Bui
Author 4: Minh Tran
Author 5: Nguyen D. Vo

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2022.01306100

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 6, 2022.

  • Abstract and Keywords
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Abstract: In recent years, object detection from space in adverse weather, incredibly foggy, has been challenging. In this study, we conduct an empirical experiment using two de-hazing methods: DW-GAN and Two-Branch, for removing fog, then eval-uate the detection performance of six advanced object detectors belonging to four main categories: two-stage, one-stage, anchor-free and end-to-end in original and de-hazed aerial images to find the best suitable solution for vehicle detection in foggy weather. We use the UIT-DroneFog dataset, a challenging dataset that includes a lot of small, dense objects captured in various altitudes, as the benchmark to evaluate the effectiveness of approaches. After experiments, we observe that each de-hazing method has different impacts on six experimental detectors.

Keywords: Foggy weather; vehicle detection; DWGAN; two-branch; YOLOv3; sparse R-CNN; deformable deter; cascade R-CNN; crossDet; adverse weather

Khang Nguyen, Phuc Nguyen, Doanh C. Bui, Minh Tran and Nguyen D. Vo, “Analysis of the Influence of De-hazing Methods on Vehicle Detection in Aerial Images” International Journal of Advanced Computer Science and Applications(IJACSA), 13(6), 2022. http://dx.doi.org/10.14569/IJACSA.2022.01306100

@article{Nguyen2022,
title = {Analysis of the Influence of De-hazing Methods on Vehicle Detection in Aerial Images},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.01306100},
url = {http://dx.doi.org/10.14569/IJACSA.2022.01306100},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {6},
author = {Khang Nguyen and Phuc Nguyen and Doanh C. Bui and Minh Tran and Nguyen D. Vo}
}


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