A REVIEW OF OBJECT DETECTION TECHNIQUES

One of the most important tasks in computer vision is object detection, particularly involves, Finding and recognizing objects in an image or video.Over the years,machine learning (ML) techniques,particularly deep learning approaches, have significantly enhanced the accuracy and efficiency of object detection systems.This paper provides an in-depth exploration of object detection using ML, focusing on the evolution of algorithms from classical approaches such as traditional feature-based methods to contemporary deep learning techniques like Convolutional Neural Networks (CNNs).Data preprocessing,feature extraction,object localization,and classification are some of the vital components in the object detection processes. Furthermore, the paper discusses the challenges associated with real-time detection, scalability, and robustness across different environments.The paper concludes with an outlook on the future of object detection,including potential applications in autonomous vehicles,surveillance,and healthcare