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- Title
Small objects detection in UAV aerial images based on improved Faster R-CNN.
- Authors
WANG Ji-wu; LUO Hai-bao; YU Peng-fei; LI Chen-yang
- Abstract
In order to solve the problem of small objects detection in unmanned aerial vehicle (UAV) aerial images with complex background, a general detection method for multi-scale small objects based on Faster region-based convolutional neural network (Faster R-CNN) is proposed. The bird's nest on the high-voltage tower is taken as the research object. Firstly, we use the improved convolutional neural network ResNetl01 to extract object features, and then use multi-scale sliding windows to obtain the object region proposals on the convolution feature maps with different resolutions. Finally, a deconvolution operation is added to further enhance the selected feature map with higher resolution, and then it taken as a feature mapping layer of the region proposals passing to the object detection sub-network. The detection results of the bird's nest in UAV aerial images show that the proposed method can precisely detect small objects in aerial images.
- Subjects
CONVOLUTIONAL neural networks; BIRD nests
- Publication
Journal of Measurement Science & Instrumentation, 2020, Vol 11, Issue 1, p11
- ISSN
1674-8042
- Publication type
Article
- DOI
10.3969/j.issn.1674-8042.2020.01.002