Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

Researchers at Tsinghua University developed PriorFusion, a unified framework that integrates semantic, geometric, and ...

Introduction: Automated apple harvesting is hindered by clustered fruits, varying illumination, and inconsistent depth perception in complex orchard environments. While deep learning models such as ...

Glittering new James Webb telescope image shows an 'intricate web of chaos' — Space photo of the week The James Webb telescope proves Einstein right, 8 times over — Space photo of the week Webb ...

This repository presents a lightweight, zero-shot segmentation pipeline using a pretrained DINO Vision Transformer and unsupervised clustering. The approach requires no labeled data or additional ...

Abstract: In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the ...

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...

Threshold-based segmentation by selecting a target color vector in one of six color spaces (RGB, HSV, CIELAB, CIEXYZ, YCbCr or YIQ (NTSC)) and isolating pixels within a user-specified tolerance.