Blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) is a cornerstone of non-invasive brain function investigation, yet its ...

Explainable AI was particularly valuable in validating the predictions. The Grad-CAM and Class Activation Mapping methods ...

The review reveals that supervised learning dominates AI-driven agriculture, accounting for nearly 60 to 88 percent of all ...

In a groundbreaking development at the intersection of artificial intelligence (AI) and medicine, Tobi Titus Oyekanmi, a ...

Yann LeCun is famously pessimistic on whether LLMs can get us to AGI, but he also seems to be pessimistic about the ...

In 2008, Pietro Perona , Caltech's Allen E. Puckett Professor of Electrical Engineering, was on sabbatical in Italy, enjoying a cappuccino in a ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a Quantum Convolutional Neural Network (QCNN) based on hybrid quantum-classical learning and ...

AI algorithm has achieved remarkable accuracy in detecting cardiac amyloidosis, outperforming traditional diagnostic methods.

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ...

In an earlier collaborative project, Ceva worked with CERN on the trigger system of the Large Hadron Collider (LHC), a sophisticated real-time filtering mechanism that deals with the torrent of ...

Zehong Wang, Xiaolong Han, Yanru Chen, Xiaotong Ye, Keli Hu, Donghua Yu (2022) Prediction of willingness to pay for airline seat selection based on improved ensemble learning Airlines have launched ...

I have come across various ways of defining Artificial Neural Networks (ANNs). Many of them miss a fundamental characteristic of theirs. An ANN is a machine learning model. Like all machine learning ...