publication . Conference object . Preprint . Other literature type . 2017

a deep learning approach to drone monitoring

Chen, Yueru; Aggarwal, Pranav; Choi, Jongmoo; Kuo, C.-C. Jay;
Open Access
  • Published: 01 Dec 2017
  • Publisher: IEEE
Abstract
A drone monitoring system that integrates deep- learning-based detection and tracking modules is proposed in this work. The biggest challenge in adopting deep learning methods for drone detection is the limited amount of training drone images. To address this issue, we develop a model-based drone augmentation technique that automatically generates drone images with a bounding box label on drone's location. To track a small flying drone, we utilize the residual information between consecutive image frames. Finally, we present an integrated detection and tracking system that outperforms the performance of each individual module containing detection or tracking onl...
Subjects
free text keywords: Detector, Bounding overwatch, Computer vision, Minimum bounding box, Deep learning, Synthetic data, Computer science, Tracking system, business.industry, business, Residual, Artificial intelligence, Drone, Computer Science - Computer Vision and Pattern Recognition

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publication . Conference object . Preprint . Other literature type . 2017

a deep learning approach to drone monitoring

Chen, Yueru; Aggarwal, Pranav; Choi, Jongmoo; Kuo, C.-C. Jay;