A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling energy-efficient self-organizing maps without external arithmetic circuits. Memristors, ...

MLB pitchers have a ridiculous number of tools at their disposal. They throw triple-digit fastballs, rip high-spin breaking balls, and show off pinpoint command. Although these are the most visible – ...

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, ...