YOLOv8 (You Only Look Once version 8) is the latest iteration of the YOLO family of object detection models, known for its high speed and accuracy. It builds upon previous versions by incorporating advanced features such as better backbone architectures and improved training techniques, making it highly efficient for real-time object detection tasks. YOLOv8 can detect multiple objects in images or videos in a single forward pass, enabling applications in fields like autonomous driving, surveillance, healthcare, and robotics. Its flexibility and performance make it a popular choice for both research and industrial applications.
Object detection is a computer vision technique in machine learning that involves identifying and locating objects within an image or video. Unlike image classification, which assigns a label to an entire image, object detection not only classifies objects but also draws bounding boxes around them to specify their exact locations. This task is crucial for applications like autonomous driving, surveillance, and image analysis, where understanding the context and position of objects is essential.
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