Vehicles and pedestrians can move freely like "ghosts"... This is not a science fiction story, but a function brought by a ...

Compressed sensing technology is a novel signal processing theory that enables sampling and reconstruction of signals at rates far below the Nyquist sampling theorem. The EALISTA algorithm, as a key ...

The explosion of machine learning (ML) model size has led to its execution on distributed clusters at a large scale. Many works have tried to optimize the process of producing collective algorithms ...

SCE-UA is a lightweight Python package implementing the Shuffled Complex Evolution (SCE-UA) algorithm for global optimization. Designed primarily for hydrological model calibration, it leverages NumPy ...

Here, we present a model-based deep learning framework for time-resolved imaging in multi-shot computational microscopy. Building upon the plug-and-play (PnP) optimization theory, our approach ...

A team of researchers from the University of Professional Studies, Accra, led by Dr. Augustina Dede Agor, has completed one of the most detailed global reviews to date on the integration of artificial ...

Second, when a roadside unit fusion (RSU) is unable to handle a task, the automatic tagging (AT) algorithm will tag the RSU, preparing for the optimization of subsequent RSU. Finally, the Nash ...

Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm Provisionally accepted ...