Generative artificial intelligence (GenAI) is now a reality in higher education, with students and professors integrating chatbots into teaching, learning and assessment. But this isn't just a ...
WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Deep learning techniques can enhance diagnosis of Meniere disease (MD) and severity grading, according to a study published ...
Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch ...
High-temperature proton exchange membrane fuel cells (HT-PEMFCs) are highly promising for next-generation aviation, as they can operate above 160 °C and tolerate impurities in the fuel. However, they ...
Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
Abstract: The integration of wind power into microgrids significantly increases the complexity of the microgrid’s dynamical behavior and introduces higher levels of uncertainty. This paper addresses ...
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 ...
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