Yun Yang, Longwei Li, Siyan Gao, Han Bai, Wancheng Jiang. Objects Detection from High-Resolution Remote Sensing Imagery Using Training-Optimized YOLOv3 Network[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1601002
- Laser & Optoelectronics Progress
- Vol. 58, Issue 16, 1601002 (2021)
Fig. 1. Principle of YOLO model for object detection
Fig. 2. Our optimized YOLOv3 model training flowchart
Fig. 3. Three objects contained in the RSOD dataset
Fig. 4. RSOD dataset augmentation processing. (a)Image flipping along X axis; (b)image cropping; (c) image rotation; (d) image saturation adjustment
Fig. 5. Labeling sample of dataset using Labeling software. (a) Original image; (b) labeled image (true object bounding box)
Fig. 6. Comparison of the three basic sizes of anchor boxes before and after our training optimization. (a) Anchor boxes from traditional YOLOv3 model; (b) anchor boxes from our clustered augmented dataset
Fig. 7. Comparison of the detection results between the traditional and our optimized YOLOv3 models. (a)--(c) Traditional YOLOv3 model; (d)--(f) our optimized YOLOv3 model
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Table 1. YOLOv3 model object detection result before and after optimization
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Table 2. Evaluation results using the traditional and optimized YOLOv3 models
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