Microgrids play a growing role in modern power systems, supporting renewable integration, local resilience, and decentralized energy management. Yet as renewable penetration rises, maintaining stable ...
Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Abstract: Despite the wide variety of applications and use cases that can be solved with the help of machine learning algorithms, researchers have yet to develop a general artificial intelligence ...
In a study titled Recent Applications of Machine Learning Algorithms for Pesticide Analysis in Food Samples, published in the ...
This is an important work implementing data mining methods on IMC data to discover spatial protein patterns related to the triple-negative breast cancer patients' chemotherapy response. The evidence ...
Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...
Recent research (2024-2025) consistently demonstrates the advantages of integrated AI-VR training: Knowledge Acquisition: ...
Low-rank data analysis has emerged as a powerful paradigm across applied mathematics, statistics, and data science. With the rapid growth of modern datasets in size, dimensionality, and complexity, ...
Abstract: This study explores the application of convolutional neural networks (CNNs) in financial time series forecasting, specifically within the stock market domain. Given the dynamic and irregular ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results