Semantic Segmentation
Semantic Segmentation is a computer vision technique that assigns a class label to every pixel in an image, allowing an AI system to identify which pixels belong to specific categories.
What is Semantic Segmentation?
Semantic segmentation divides an image into meaningful regions by assigning the same class label to pixels belonging to the same category. For example, in a street scene, pixels can be classified as road, vehicle, pedestrian, building, or sky without distinguishing between individual objects of the same class.
Why is Semantic Segmentation Important?
Semantic segmentation provides detailed pixel-level understanding of visual data. This enables AI systems to analyze the precise location and boundaries of different categories, supporting applications that require more detailed visual information than image-level classification.
Common use cases
Semantic Segmentation is commonly used in autonomous driving, medical imaging, satellite imagery, scene understanding, agriculture, and other computer vision applications.