Abstract: Several applications in different engineering areas require the computation of the Euclidean distance, a quite complex operation based on squaring and ...

Machine learning has expanded beyond traditional Euclidean spaces in recent years, exploring representations in more complex geometric structures. Non-Euclidean representation learning is a growing ...

Abstract: Euclidean distance transforms are fundamental in image processing and computer vision, with critical applications in medical image analysis and computer graphics. However, existing ...

ABSTRACT: Purpose: This study describes a machine-learning approach utilizing patients' anatomical changes to predict parotid mean dose changes in fractionated radiotherapy for head-and-neck cancer, ...

This Jupyter notebook demonstrates image segmentation using Lazy Snapping and K-Means Clustering. It showcases how these algorithms can partition an image into segments based on pixel intensity and ...

Distance calculation is essential in various fields like physics, mathematics, engineering, geography, and everyday life. Knowing how to measure distance accurately and efficiently allows us to ...

Calculating the distance between two points is a fundamental concept in mathematics, often applied in various fields such as geometry, physics, and engineering. Understanding how to compute the ...

As anyone who’s ever been in one can attest, making a long-distance relationship work is challenging—yes, even if you’re super into each other. But despite what a skeptical friend, family member, or ...

C++ 3D Vector class and utilities for common vector operations such as euclidean distance, multiplication of vectors, dot, cross, vector-plane intersect, triangle distance, to/from cartesan & ...