Abstract: Water-land segmentation faces significant challenges due to land-water interface heterogeneity. Existing methods based on spatially constrained statistical models often yield unsatisfactory ...

Watershed, Washington state’s biggest country music festival, will not be held in 2026, according to an announcement on the festival website. “After 13 incredible years of country music and community ...

This project implements a 2D pore-throat network extraction algorithm for porous media images. It uses a modified watershed segmentation approach based on Distance Transform and H-maxima markers to ...

To address the engineering challenge of detecting fine cracks on hybrid wind turbine towers, especially against complex water seepage backgrounds, this study aims to explore optimal image segmentation ...

An app for segmentation and classification of images of cells from optical microscope. This project uses marker controlled watershed (openCv), and pretrained ResNet-50 model (tensorflow) ...

Cell segmentation is a crucial step in numerous biomedical imaging endeavors—so much so that the community is flooded with publicly available, state-of-the-art segmentation techniques ready for out-of ...

Abstract: In order to overcome the problem of over-segmentation, a novel algorithm of watershed segmentation based on morphological gradient reconstructing is proposed in this paper. In the algorithm, ...

ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...