ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

1 Department of Nephrology, the 95th Hospital of Putian in China RongTong Medical Health Corporation, Putian, China 2 Department of Rheumatology and Immunology, the 95th Hospital of Putian in China ...

A new study offers insight into the health and lifestyle indicators - including diet, physical activity and weight - that align most closely with healthy brain function across the lifespan. The study ...

GameSpot may get a commission from retail offers. Machine-learning and artificial intelligence systems are some of the most-talked-about technologies in gaming--and across a variety of other ...

🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) ...

Inspired by the brain, neural networks are essential for recognizing images and processing language. These networks rely on activation functions, which enable them to learn complex patterns. However, ...

Cutting-edge researchers Tomohito Amano and Shinji Tsuneyuki at the University of Tokyo, alongside Tamio Yamazaki from CURIE (JSR-UTokyo Collaboration Hub), have unveiled a machine learning model that ...

Machine learning and artificial intelligence methods are often referred to as “black boxes” when compared with traditional regression-based approaches. However, both traditional and machine learning ...

ABSTRACT: This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from ...