Results 161 to 170 of about 83,310 (315)
Hypergraph-based contrastive learning for enhanced fraud detection. [PDF]
Wang Q, Shen Y, Dong H.
europepmc +1 more source
Deviation‐Guided Attention for Semi‐Supervised Anomaly Detection With Contrastive Regularisation
ABSTRACT Anomaly detection (AD) aims to identify abnormal patterns that deviate from normal behaviour, playing a critical role in applications such as industrial inspection, medical imaging and autonomous driving. However, AD often faces a scarcity of labelled data. To address this challenge, we propose a novel semi‐supervised anomaly detection method,
Guanglei Xie +6 more
wiley +1 more source
Enhancing credit card fraud detection using DBSCAN-augmented disjunctive voting ensemble. [PDF]
Ghalwash MA +3 more
europepmc +1 more source
Detecting automobile insurance fraud using a novel penalty-driven feature selection method with particle swarm optimization and machine learning classifiers. [PDF]
Özaltın Ö, Erdemir ÖK.
europepmc +1 more source
Analysing policy success and failure in Australia: Pink batts and set‐top boxes
Abstract This article examines two Australian government programs from the Rudd/Gillard Labor government, the Home Insulation Program (HIP) and the Digital Switchover Household Assistance Scheme (HAS). Both became shibboleths of the Labor government's perceived waste and incompetence.
Daniel Casey
wiley +1 more source
Designing a national framework for preventing fraud in Iran's health system: a sequential mixed-methods study using qualitative analysis and Delphi consensus. [PDF]
Vafaee Najar A, Hooshmand E.
europepmc +1 more source

