Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
BMJ

Protocol for the OPTIMSE-1 randomised clinical trial to test specialist-led identification and management of cardio-renal-metabolic-pulmonary disease in machine learning ...

Introduction People identified as higher risk by a machine learning algorithm (Future Innovations in Novel Detection of Atrial Fibrillation [FIND-AF]) are at increased risk of ...
The New York Times

These Tools Say They Can Spot A.I. Fakes. Do They Really Work?

Artificial intelligence detectors are increasingly used to check the veracity of content online. We ran more than 1,000 tests and found several strengths and plenty of weaknesses. By Stuart A.
IEEE

Enhancing Community Detection in Complex Social Networks With a Hybrid Genetic Algorithm

Abstract: Community detection in social networks is a fundamental challenge in network science driven by the increasing complexity of online platforms. In a given network, a community is a group of ...
IEEE

A Novel Community Detection Algorithm Based on Node Propagation and Attraction

Abstract: High-quality community detection in complex networks typically relies on the similarity between nodes to select communities. However, when a node exhibits the same similarity with different ...
FedScoop

CBP still working toward anomaly detection algorithms at the border

Customs and Border Protection is continuing to work on developing algorithmic systems to conduct automated inspections of vehicles at the border, with the providers of these systems still in the ...