Target detection method combined with lightweight network

Abstract

The invention provides a target detection method combined with a lightweight network, and aims to solve the problem of balancing the detection speed and precision of a small target such as UAV, realize the lightweight of a network model, and provide possibility for target detection on an embedded platform. According to the characteristics of small size, high flight speed and the like of an unmanned aerial vehicle, the invention provides a quick target detection algorithm improved in combination with a lightweight network. The YOLOv3 algorithm for detecting three feature scales is expanded to five feature scales for detection, and the detection performance of small target scenes such as unmanned aerial vehicles is improved. A lightweight feature extraction network is constructed in combination with a Ghost module in a lightweight network, and in order to further improve the detection performance of the network, a channel attention mechanism is added to suppress unfavorable information. According to the invention, a UAV data set of an urban background is generated for training. Experimental results show that the method provided by the invention can effectively improve the detection precision of the UAV under the complex city background and meet the real-time requirement.

Description

technical field [0001] The invention relates to the fields of deep learning and target detection, in particular to a target detection method combined with a lightweight network. Background technique [0002] With the development of science and technology, various kinds of UAVs have appeared one after another. Among them, civilian UAVs have developed rapidly and are widely used in various fields. The application of UAVs can greatly reduce the cost of high-altitude operations. Unique advantages, UAV technology brings convenience to people's life, but also brings many potential threats to the country and society. The supervision of drones has become the focus of social attention. UAVs have the characteristics of small size, fast flight speed, and high rotation. Traditional target detection methods are difficult to meet the requirements. The target detection method based on deep neural network shows its powerful detection performance. In recent years, the rapid development of ...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a target detection method combined with a lightweight network to solve the problem that the detection and supervision of unmanned aerial vehicles are very difficult. Experiments have proved that the method proposed by the present invention can effectively improve UAVs. The detection accuracy and real-time requirements in the complex urban background have realized the light weight of the target detection algorithm, which provides the possibility to realize the target detection on the embedded platform

Images