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

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 ...

Every protein in the body is encased in a water shell that directs protein structure, provides vital stability and steers function. Because of this, water molecules represent a powerful but largely ...

Since 1997, New York City has purchased more than 1,800 properties to protect its drinking water. No longer. By Tim Heffernan The largest single taxpayer in the Catskills is New York City. To protect ...

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 ...