Pixel Wise Classification

Pixel-wise classification aims to assign a class label to each pixel in an image, enabling detailed scene understanding. Current research emphasizes improving accuracy and robustness, particularly for challenging scenarios like small objects and noisy data, using diverse approaches including U-Net architectures, tree-based methods, and generative models integrated with physical constraints. This technique finds applications in diverse fields, from ecological monitoring and urban planning (analyzing hyperspectral and aerial imagery) to material science (identifying graphene layers), driving advancements in both data analysis and environmental/material characterization.