Enhancing Object Detection with AI-Driven Deep Learning Techniques

Abstract

Object detection plays a crucial role in computer vision and is vital for various applications, such as autonomous vehicles. Over the past five decades, object detection techniques have advanced considerably, resulting in many innovative and successful approaches. Today, object recognition methods are broadly categorized into traditional machine learning techniques and deep learning methods. This article provides an overview of object detection techniques, beginning with a summary of traditional machine learning-based methods. It then explores two leading deep learning approaches, R-CNN and YOLO, before concluding with a comparison and discussion of these methods.