A Perspective Study of Real-Time Object Detection Using Deep Learning by Applying Design Thinking Approach

Object detection using deep learning addresses challenges in real-world image conditions, such as noise and blurring, impacting object detection performance. Employing the You Only Look Once (YOLO) approach, our objective is to enhance detection accuracy and speed. YOLO's advantages over other algorithms, such as complete image analysis and faster processing, make it a preferred choice. Object detection, crucial in various applications like face and vehicle detection, is fundamental in security systems and driverless cars. The project aims to detect and count similar objects in video, image, and lives webcam scenarios. Object recognition tasks, including image classification and localization, will be explored for diverse practical applications. This research contributes to advancing computer vision technologies, fostering creative applications in fields through the efforts of programmers and developers. The project's significance lies in its potential impact on security, surveillance, and emerging technologies.