An online training method for realizing target detection on unmanned equipment

Abstract

The invention discloses an online training method for realizing target detection on unmanned equipment, and solves the problems that target detection and network training cannot be performed in parallel in real time and the detection result is inaccurate in the prior art. The method comprises the following implementation steps: respectively designing a target detection network according to the characteristics of a panoramic video, a visible light video and an infrared video, and carrying out preliminary training; Judging whether target related images and information exist in the information transmitted into the unmanned equipment or not; Selecting a corresponding image library according to the new target image and the information, and expanding the image library; And carrying out online training on each target detection network, finally obtaining new network structure parameters, and replacing a previous network parameter file. According to the invention, an on-line training mode is adopted, target detection and network training can be performed in parallel in real time, the target detection precision is higher, and the method can be used for unmanned equipment in an operation state.

Description

technical field [0001] The invention belongs to the technical field of image processing, and mainly relates to online training of unmanned equipment target detection, in particular to an online training method for realizing target detection on unmanned equipment, which can be used to perform target detection of various types of images on unmanned equipment Online training of detection networks. Background technique [0002] With the development and progress of artificial intelligence, unmanned equipment occupies an important position in people's production and life, and plays an important role in many fields such as remote sensing mapping, disaster rescue, and environmental protection testing. Unmanned equipment often needs functions such as target recognition and obstacle avoidance during routine operation, so it is necessary to design an online training method for image-based target detection networks. Target detection is to detect the target area and perform image segmen...

AI Technical Summary

Problems solved by technology

However, the sample values ​​obtained by offline training are relatively limited, and it is impossible to obtain a more accurate target area according to the current requirements of the user.

In the existing online training technology of target detection, only the method of using traditional target detection algorithm for online training of target detection is considered. The patent proposes an online training method using a target detection algorithm based on artificial threshold selection. This method improves the accuracy of target detection results to a certain extent by increasing the number of detection samples. In terms of selection, the subjective factors are strong, human intervention is required, and the traditional method has a large amount of calculation, which makes the speed of target detection not fast enough, and the detection accuracy is not high enough, and it is impossible to achieve real-time target detection and online training of the network. The effect of high detection results

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