Image segmentation refers to the process of partitioning a digital image into distinct regions that correspond to objects or areas of interest. Classical approaches can be grouped into thresholding, ...
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 ...
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 ...
A San Francisco nonprofit has purchased 11,000 acres of land at the headwaters of the Trinity River from a timber company, aimed at protecting the source of the massive Trinity Reservoir. The Pacific ...
Leeron is a New York-based writer who specializes in covering technology for small and mid-sized businesses. Her work has been featured in publications including Bankrate, Quartz, the Village Voice, ...
This project implements three image segmentation algorithms - Region Growing, Watershed, and K-Means, to separate an object from its background, evaluated using the Jaccard Similarity Coefficient.
Abstract: Watershed algorithm is applied widely to image segmentation for its fast computing and high accuracy in locating the weak edges of adjacent regions. But classical watershed segmentation is ...
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