Blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) is a cornerstone of non-invasive brain function investigation, yet its ...
Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...
In a groundbreaking development at the intersection of artificial intelligence (AI) and medicine, Tobi Titus Oyekanmi, a ...
Abstract: This paper thoroughly examines the employment of the highly potent EfficientNetB0 convolutional neural network (CNN) architecture for image-based growth phase classification of maize crops, ...
Abstract: Aiming at the problem that traditional personalized learning path planning methods rely on expert experience and are difficult to accurately capture the deep relationship between learners' ...
Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn hidden patterns from ...
Abstract: Fire hazards have been a source of huge losses in households, industries, and public places. The conventional fire safety system integrates embedded systems such as sensors and ...
Abstract: Oil and gas distribution through undersea pipelines requires continuous monitoring, especially when transmitting these resources through undersea pipelines, as operational failures can lead ...
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