Developments in object detection and image segmentation
Posted: Thu Feb 06, 2025 3:17 am
This competition was called "a showdown between human wisdom and artificial intelligence", and attracted the attention and heated discussions of hundreds of millions of people around the world. At that time, this event caused a huge sensation around the world, allowing many people to begin to realize the potential of artificial intelligence and also allowing artificial intelligence technology to quickly spread around the world.
Object detection and image segmentation are two important tasks in computer vision. In object detection, the algorithm needs to identify and frame different objects in the image and identify which category lithuania mobile database they belong to. In image segmentation, the algorithm needs to divide the image into different regions and determine which category these regions belong to. The development of deep learning has promoted progress in the field of object detection and image segmentation, especially in the use of convolutional neural networks CNNs.
In 2015, Fei-Fei Li and other researchers released the Microsoft COCO Common Objects in Context dataset, which contains a large number of images, each containing multiple objects, and each object is labeled with its location and category. This dataset has become one of the important reference datasets in the field of computer vision, and has also become a standard dataset for evaluating object detection and image segmentation algorithms.
Object detection and image segmentation are two important tasks in computer vision. In object detection, the algorithm needs to identify and frame different objects in the image and identify which category lithuania mobile database they belong to. In image segmentation, the algorithm needs to divide the image into different regions and determine which category these regions belong to. The development of deep learning has promoted progress in the field of object detection and image segmentation, especially in the use of convolutional neural networks CNNs.
In 2015, Fei-Fei Li and other researchers released the Microsoft COCO Common Objects in Context dataset, which contains a large number of images, each containing multiple objects, and each object is labeled with its location and category. This dataset has become one of the important reference datasets in the field of computer vision, and has also become a standard dataset for evaluating object detection and image segmentation algorithms.