Target detection system suitable for embedded device

Abstract

A target detection system suitable for an embedded device, comprising an embedded device () and a server (); target detection logic () running in the embedded device () is composed of a multi-layer shared base network, a private base network, and a detection module; a parameter of the shared base network directly comes from an output of an upper layer; and an image is processed by the shared base network and the private base network to obtain a feature map, and after being processed by the detection module, a result merging module merges and outputs a target detection result. The target detection system further comprises an online model self-calibration system. After collecting a sample, the embedded device () irregularly uploads the sample to the server (), and after labeling the sample by means of automatic and manual methods, the server () trains a model and updates same to the embedded device (). The target detection system can perform well in an embedded device (), uses a large-scale target detection model on a server () to complete automatic labeling which reduces workload, and completes model correction more efficiently.