AZoOptics

Deep Learning in Optical Microscopy: Advancements and Applications

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...
Computer Weekly

Transfer learning and governance help bridge healthcare AI divide

Singapore researchers show how adapting pre-trained AI models can solve data scarcity issues in countries with limited ...

Chongwei Shi Advances Biostatistical Methods and Computational Biology Through Deep Learning and Statistical Shape Analysis

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...
IEEE

A Novel Semi-Supervised Deep Transfer Learning Method With Improved Extended Isolation Forest for Bearing Fault Diagnosis

Abstract: Industrial condition monitoring leverages transfer learning to enhance equipment diagnostics. However, existing deep transfer learning (DTL) methods face a critical challenge, which still ...
Frontiers

An optimized transfer learning approach integrating deep convolutional feature extractors for malaria parasite classification in erythrocyte microscopy

Background: Malaria, caused by Plasmodium parasites transmitted through bites from infected female Anopheles mosquitoes, results in severe symptoms such as anemia and potential organ failure. The high ...
Hosted on MSN

What Is In-Context Learning in Deep Learning – Simple Explanation

Learn the concept of in-context learning and why it’s a breakthrough for large language models. Clear and beginner-friendly explanation. #InContextLearning #DeepLearning #LLMs Supreme Court Deals ...
Frontiers

Novel deep learning for multi-class classification of Alzheimer’s in disability using MRI datasets

Introduction: Alzheimer’s disease (AD) is one of the most common neurodegenerative disabilities that often leads to memory loss, confusion, difficulty in language and trouble with motor coordination.
Scientific Research Publishing

Gao, Q., Liu, Y., Zhao, J., et al. (2021) Hybrid Deep Learning for Dynamic Total Transfer Capability Control. IEEE Transactions on Power Systems, 36, 2733-2736.

ABSTRACT: In view of the control problem of hydrogen pressure and flow coupling in the anode subsystem of the Proton Exchange Membrane Fuel Cell (PEMFC) under dynamic load conditions, this paper ...
C&EN

Transfer-Learning Deep Raman Models Using Semiempirical Quantum Chemistry

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Biophotonic technologies such as Raman spectroscopy are powerful tools for obtaining ...