In this paper, a deep neural network model based on small target detection under UAV platform is designed. Due to the One-stage detection model like YOLO having novel structure and great industrial application potential, this paper proposes a new model of detection based on YOLOv2 structure. Faced with missed detection problem of small target, a series of improved schemes are proposed, which are suitable for small vehicles' detection under aerial view angle, and can achieve real-time detection, including dense topology and optimal pooling strategy.
|Title of host publication||2018 5th International Conference on Systems and Informatics (ICSAI 2018): Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|Publication status||Published - 03 Jan 2019|
|Event||5th International Conference on Systems and Informatics, ICSAI 2018 - Nanjing, China|
Duration: 10 Nov 2018 → 12 Nov 2018
|Name||2018 5th International Conference on Systems and Informatics, ICSAI 2018|
|Conference||5th International Conference on Systems and Informatics, ICSAI 2018|
|Period||10/11/2018 → 12/11/2018|
Bibliographical noteFunding Information:
ACKNOWLEDGMENT This work received support from Science and Technology on Electro-optic Control Laboratory and Aviation Science Foundation Project (No 20175152036). The authors are also grateful for the support of their colleagues at the Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education.
© 2018 IEEE.
Copyright 2019 Elsevier B.V., All rights reserved.
- deep learning
- vehicle detection
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Networks and Communications
- Energy Engineering and Power Technology
- Control and Systems Engineering