Image Segmentation with Convolutional Neural Networks

Image segmentation involves dividing an image into multiple regions or segments, often to identify objects or boundaries. Convolutional Neural Networks (CNNs) are widely used for this task. They learn spatial hierarchies of features from images, enabling pixel-wise classification. This means each pixel is assigned a label indicating which segment it belongs to. For example, in a self-driving car, CNNs can segment images to identify roads, pedestrians, and other vehicles, allowing the car to "understand" its surroundings. Other applications include medical image analysis for tumor detection and satellite imagery analysis for land cover classification.