ARF-YOLOv8: a novel real-time object detection model for UAV-captured images detection-Reference-Cited by-同舟云学术

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ARF-YOLOv8: a novel real-time object detection model for UAV-captured images detection

Published:2024-06-04 Issue:4 Volume:21 Page:
ISSN:1861-8200
Container-title:Journal of Real-Time Image Processing
language:en
Short-container-title:J Real-Time Image Proc

Author:

Zeng YaLin,Guo DongJin,He WeiKai,Zhang Tian,Liu ZhongTao

Funder

Shandong Provincial Technology Innovation Guidance Plan

Science and Technology SMEs Innovation Capacity Improvement Project of Shandong

National Natural Science Foundation of China

Shandong Provincial Natural Science Foundation

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11554-024-01483-z.pdf

Reference50 articles.

1. Liu, W., Quijano, K., Crawford, M.M.: Yolov5-tassel: detecting tassels in rgb uav imagery with improved yolov5 based on transfer learning. IEEE J. Select. Top. Appl. Earth Observ. Remote Sens. 15, 8085–8094 (2022)

2. Bouguettaya, A., Zarzour, H., Kechida, A., Taberkit, A.M.: Deep learning techniques to classify agricultural crops through UAV imagery: a review. Neural Comput. Appl. 34(12), 9511–9536 (2022)

3. Lu, Y., Lu, J., Zhang, S., Hall, P.: Traffic signal detection and classification in street views using an attention model. Comput. Vis. Media 4, 253–266 (2018)

4. Martinez-Alpiste, I., Golcarenarenji, G., Wang, Q., Alcaraz-Calero, J.M.: Search and rescue operation using UAVs: a case study. Expert Syst. Appl. 178, 114937 (2021)

5. Girshick, R.: Fast r-cnn. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1440–1448 (2015)

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