In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

In this video, we will understand all major Optimization in Deep Learning. We will see what is Optimization in Deep Learning ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines.

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

By fusing behavioral data, real-time analytics and generative AI, the industry is entering a new era: attention hacking at scale.

A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

With such increased predictive knowledge of solar systems, these anomaly detectors can significantly reduce costs of O&M, a major component of project economics in solar development. There is great ...