Abstract: Fault diagnosis holds significant practical importance for high performance and reliable control of induction motors. However, existing deep learning-based fault diagnosis methods demand a ...
Beijing, Jan. 05, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning ...
This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
Manufacturing technologies have been the first domain to experience this transformation. The review documents how artificial ...
Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...
Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Abstract: The proliferation of Internet of Things (IoT) devices has increased susceptibility to Distributed Denial of Service (DDoS) attacks, exposing the limitations of traditional security ...
AZoSensors on MSN
AI maps heat inside steelmaking’s critical sintering process beds
The Temporal Fusion Transformer model provides near-real-time insights into sintering temperatures, addressing critical challenges in steelmaking processes.
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