Rongqi Jiang, Zecong Ye, Yueping Peng, Guorong Xie, Heng Du. Lightweight Target Detection Algorithm for Small and Weak Drone Targets[J]. Laser & Optoelectronics Progress, 2022, 59(8): 0810006

Search by keywords or author
- Laser & Optoelectronics Progress
- Vol. 59, Issue 8, 0810006 (2022)

Fig. 1. Partial pictures of datasets. (a) Dataset A; (b) Dataset B

Fig. 2. Analysis of size of drone targets in two datasets. (a) Dataset A; (b) Dataset B

Fig. 3. Structure diagram of YOLOv4-tiny algorithm. (a) YOLOv4-tiny; (b) CSPBlock

Fig. 4. Structure diagram of DTD-YOLOv4-tiny model

Fig. 5. ShuffleNetV2 and improved backbone network structure. (a) ShuffleV2Block; (b) backbone network of ShuffleNetV2; (c) backbone network of proposed algorithm

Fig. 6. FPN structure comparison of different detection models. (a) YOLOv4-tiny; (b) YOLOv4-tiny (YOLO-Head enhancement); (c) DTD-YOLOv4-tiny

Fig. 7. Working principle of reorg_layer

Fig. 8. Working principles of sub-pixel Conv and sub-pixel. (a) Sub-pixel Conv; (b) sub-pixel

Fig. 9. Comparison of accuracy and detection speed of different target detection models under different datasets. (a) Dataset A; (b) Dataset B

Fig. 10. Comparison of partial detection results of test set on different datasets. (a) YOLOv4-tiny (Dataset A); (b) DTD-YOLOv4-tiny (Dataset A); (c) YOLOv4-tiny (Dataset B); (d) DTD-YOLOv4-tiny (Dataset B)
|
Table 1. Performance comparison of different algorithms in MS COCO dataset
|
Table 2. Ablation experiment results of DTD-YOLOv4-tiny algorithm
|
Table 3. 4 Performance comparison of different algorithms on Dataset A
|
Table 4. Performance comparison of different algorithms on Dataset B

Set citation alerts for the article
Please enter your email address