Design of Multi-object Detection and Tracking System Based on Neural Network Algorithm
In today's era,technology is rapidly developing,multi-object detection and tracking systems are playing an increasingly important role in various industries.The core of such systems is to analyze image or video data using algorithms to achieve simultaneous detection and tracking of multiple objects.This paper will provide a detailed exposition of the design and implementation process of the system,covering aspects such as system architecture,image preprocessing,feature extraction and constant module detection algorithms.Specifically,this paper elaborates on the design and implementation of a multi-object detection and tracking system based on neural network algorithms.It includes the overall system architecture,design of the image preprocessing module,selection and optimization of the backbone network for feature extraction,and demonstrates its effectiveness and efficiency through system testing and validation.
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