Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...

Machine learning (ML) is rapidly emerging as a powerful tool to improve the safety, reliability, and long-term performance of marine structures exposed to harsh ocean environments. This study presents ...

This important study combines optogenetic manipulations and wide-field imaging to show that the retrosplenial cortex controls behavioral responses to whisker deflection in a context-dependent manner.

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Abstract: In this study, a hyperparameter (HP) tuning method for simulated annealing (SA) is proposed. In recent years, annealing machines, i.e., non-Neumann architecture computers inspired by the ...

Abstract: Reliable tea leaf quality classification is vital for maintaining product consistency and consumer satisfaction. However, traditional assessment techniques—such as physicochemical analysis ...

A Marshall University – University of Missouri team has reported a web-based deep-learning platform that combines six common ...

The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...

Spatiotemporal Evolution Patterns and Intelligent Forecasting of Passenger Flow in Megacity High-Speed Rail Hubs: A Case ...

A comprehensive tutorial repository for learning deep learning model optimization techniques, including network tuning, backpropagation optimization, overfitting management, and root cause analysis.