Performance Analysis of Different Types of Nn Models for Target Recognition

Abstract

The objective of this research is to conduct a comprehensive performance analysis of various types of neural network (NN) models for target recognition. Specifically, this study focuses on evaluating the effectiveness and efficiency of yolov8n, yolov8s, yolov8m models in target recognition tasks. Leveraging cutting-edge technologies such as OpenCV, the research is aimed at developing a robust methodology for assessing the performance of these NN models. Through meticulous analysis, this study aims to provide insights into the strengths and weaknesses of each model, facilitating informed decision-making for practical applications1. This paper presents the process of designing and conducting the performance analysis. The study discusses the implications of the findings for future developments in target recognition systems.