Abstract: This paper introduces an enhanced U-Net network designed to extract fine crack features against complex backgrounds and balance crack pixel categories for bridge crack segmentation.

Task: Classify every pixel of a synthetic desert offroad image into one of 10 semantic classes: Background, Trees, Lush Bushes, Dry Grass, Dry Bushes, Ground Clutter, Logs, Rocks, Landscape, and Sky.

Microsoft’s introduction of the Maia 200 adds to a growing list of hyperscaler-developed processors, alongside offerings from AWS and Google. These custom AI chips are largely designed to improve ...

Abstract: A new edge detection method is proposed for the inspection of navel orange surface defects, enabling precise defect localization, classification type, and size estimation. This study ...