Recent years have witnessed the unprecedented development of Industry 4.0 and the Industrial Internet of Things. These two ...

A deep learning project that applies transfer learning with pre-trained convolutional neural networks (CNNs) to classify brain MRI scans into three Alzheimer's Disease stages. By leveraging ...

Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

Mingai Li, received her B.Sc. degree and M.Sc. degree from Daqing Petroleum Institute, Heilongjiang, China, in 1987 and 1990 respectively, and Ph.D. degree from Beijing University of Technology, ...

Abstract: Leveraging the power of deep reinforcement learning (DRL) and strategic knowledge transfer, our study introduces PIRA-DRL-DTRL, a novel approach to optimizing resource allocation in emerging ...

Accurate prediction of joint torque is critical for preventing injury by providing precise insights into the forces acting on joints during activities. Traditional approaches, including inverse ...

Abstract: Dear Editor, This letter presents a new transfer learning framework for the deep multi-agent reinforcement learning (DMARL) to reduce the convergence difficulty and training time when ...

Deep-transfer-learning–based NLP models were retrospectively trained and tested with serial, free-text CT reports, and survival information of consecutive patients diagnosed with pancreatic cancer in ...