IEEE

An Energy-Based Method for Predicting Battery Aging Using Newly Constructed Features in Fractal-Gradient-Enhanced LSTM Networks

Abstract: As an effective way, the incremental capacity analysis (ICA) method has been widely adopted in the battery aging prediction field. Using the aging features from the ICA method, the success ...
Medscape

AI-Based Algorithm Aids B-Line Detection in Lung Ultrasound

According to a new study, the use of an artificial intelligence-based "You Only Look Once (YOLO)" algorithm showed high precision in detecting B lines on lung ultrasound (LUS) images, with substantial ...
Marketing

How AI Is Impacting Account-Based GTM Programs

How is AI being used in account-based go-to market (GTM) programs? How will AI impact these programs in the future? What are the top barriers to AI adoption? To find out, researchers at ForgeX and ...
Frontiers

Plug-and-play low-rank tensor completion and reconstruction algorithms with improved applicability of tensor decompositions

1 Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan 2 RIKEN Center for Advanced Intelligence Project, Tokyo, Japan In this paper, we propose a new unified optimization ...
GitHub

gradient-based-learning

Add a description, image, and links to the gradient-based-learning topic page so that developers can more easily learn about it.
Frontiers

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

1 School of Information Engineering, Anhui University of Chinese Medicine, Hefei, China 2 School of Pharmaceutical Economics and Management, Anhui University of Chinese Medicine, Hefei, China ...
IEEE

Fuzzy Fitness Distance Balance Gradient-Based Optimization Algorithm (fFDBGBO): An Application to Design and Performance Optimization of PMSM

Abstract: The exceptional properties of Permanent Magnet Synchronous Motors (PMSMs), including their small construction, high power-torque density, and high efficiency, make them one of the most ...