Computer Vision Application Analysis based on Object Detection

Object detection is a computer vision method that allows for the identification and localization of specific classes objects in images or videos. It goes beyond simple object classification helps provide better understanding question. has numerous applications, including automating business processes like inventory management retail [1]. can detect occupy between 2% 60% an image's area clusters as single entity. Additionally, it localize at high speeds, typically greater than 15 frames per second. Vehicle crucial component development autonomous vehicles, enabling them to identify perceive their environment. involves identifying locating vehicles image video various applications surveillance security systems. There are different techniques models detection, traditional processing methods modern deep learning networks. Traditional Viola-Jones, SIFT, histogram oriented gradients do not require historical data training unsupervised. Popular tools OpenCV be used these techniques. On other hand, networks CNN, RCNN, YOLO, ResNet, RetinaNet, MANet supervised efficient detection. Key Words: Deep learning, OpenCV,