Semi-supervised Learning: A machine learning approach that utilises both labelled and unlabelled data to improve learning accuracy, particularly useful when comprehensive labelled datasets are scarce.

Bespoke fraud ML models are powered by algorithms that learn from historical data, picking up on behaviors and characteristics commonly associated with fraud.

demonstrate superior performance compared to conventional non-machine learning approaches when used to detect lies and deception. Subscribe to our newsletter for the latest sci-tech news updates. They ...

Truly high-quality forgery is complex and expensive but when you consider the value of, for example, celebrity signatures, you can see why the effort would pay off.

Ways to detect a poisoned machine learning dataset The good news is that organizations can take several measures to secure training data, verify dataset integrity and monitor for anomalies to ...

According to new research from Drexel University, current methods for detecting manipulated digital media will not be effective against AI-generated video; but a machine-learning approach could be the ...

Image forgery detection techniques have evolved into a sophisticated field that spans traditional methods and state‐of‐the‐art deep learning approaches. Researchers focus on identifying ...