Convolutional neural network is used in target contour extraction

Target contour extraction is a key task in the field of image processing, which is of great significance for applications such as image segmentation, object detection, and scene understanding. Traditional methods are often limited by complex scenarios and changing target shapes, and their effects may be unstable. In recent years, with the vigorous development of deep learning technology, Convolutional Neural Network (CNN) has shown significant advantages intarget contour extraction tasks due to its powerful feature representation and learning capabilities. In this paper, the loss function is used, and the loss function mechanism adopted is Softmax, which is especially suitable for multi-classification problems and is widely used in supervised and unsupervised learning scenarios.