With the rapid growth of the international banking industry, bank failures can lead to severe economic losses and social ...

China's Volt Typhoon is on your network Admission impossible: NSA, CISA brass absent from RSA Conf How to survive as a CISO aka 'chief scapegoat officer' Still, the intruders' use is similar to the ...

In previous study, Lien et al. (2023) investigates the use of convolutional neural networks (CNNs) to classify the severity of AD based on SPECT (single-photon emission computed tomography) images.

Constrained deep learning is an advanced approach to training deep neural networks by incorporating domain-specific constraints into the learning process.

AI models learn through a process called training, where data is passed through a neural network to identify patterns. The model makes predictions, compares them to actual results, and adjusts ...

The np_bnn library is a Python implementation of Bayesian neural networks for classification, using the Numpy and Scipy libraries. The program is used in our arXiv paper. The npBNN package implements ...

Recent studies highlight the effectiveness of AI techniques, such as convolutional neural networks (CNNs) and support vector machines (SVMs), achieving detection accuracy rates of up to 95% across ...

Penn Engineers have developed the first programmable chip that can train nonlinear neural networks using light—a breakthrough that could dramatically speed up AI training, reduce energy use and even ...

Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, You’anmenwai, Xitoutiao No.10, Beijing, P. R. China Beijing Municipal Key Laboratory of Clinical ...