eLife

New idtracker.ai rethinks multi-animal tracking as a representation learning problem to increase accuracy and reduce tracking time

Identification of each animal in a collective becomes possible even when individuals are never all visible simultaneously, enabling faster and more accurate analysis of collective behavior.
GitHub

GitHub - wsiqz/customer-segmentation: Customer segmentation using RFM analysis, UMAP, and clustering · GitHub

📌 Project Overview This project focuses on customer segmentation for an online gift store using RFM analysis and clustering techniques. The goal is to identify distinct customer groups based on ...
IEEE

Customer Segmentation Using Machine Learning

Abstract: Customer segmentation is a method that uses un- supervised machine learning to segment customers by common characteristics, behaviors, and wants. This technique enables companies to market ...
IEEE

Improved Mask R-CNN based on attention-enhanced pyramid and edge refinement: high-precision instance segmentation for industrial disordered parts

Abstract: Aiming at the problems of scattered distribution of different parts on the factory production line, and poor accuracy of traditional methods, a chaotic parts recognition model that improves ...
iaea.org

New IAEA Research Project Uses Machine Learning to Better Predict Polymer Changes under Radiation

Azillah Binti Othman, IAEA Department of Nuclear Sciences and Applications Ayhan Evrensel, IAEA Department of Nuclear Sciences and Applications The IAEA is inviting research organizations to join a ...