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

🔥News: A PyTorch version of this package can be found in ULTRA_pytorch. This is an Unbiased Learning To Rank Algorithms (ULTRA) toolbox, which provides a codebase for experiments and research on ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

To address the issues of strong subjectivity and difficulty in feature extraction that are inherent to traditional frequency response analysis methods used for diagnosing transformer winding ...

The rising popularity of electric vehicles (EVs) is driving a transition in transportation toward electric vehicles (EVs), which presents both opportunities and problems for energy management systems.

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...

Artificial intelligence (AI) machine learning is helping to transform many industries as an assistive tool for scientists. Researchers have published in Digital Discovery, a The Royal Society of ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

Abstract: Most research studies on deep learning (DL) applied to the physical layer of wireless communication do not put forward the critical role of the accuracy-generalization trade-off in ...

With the current buzz around artificial intelligence (AI), it would be easy to assume that it is a recent innovation. In fact, AI has been around in one form or another for more than 70 years. To ...

Machine learning (ML) algorithms are now widely used across the IT infrastructures of forward-thinking companies and academic institutions. In an effort to optimize computing resource costs and ...

The clinical applications of brain age prediction have expanded, particularly in anticipating the onset and prognosis of various neurodegenerative diseases. In the current study, we proposed a deep ...