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 ...
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 ...
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 ...
Frontiers

Deep learning based AI-driven teaching models in Chinese high school English class: a case study of reading lessons

The traditional English teaching model placed more emphasis on the rote memorization of knowledge, with less focus on encouraging deeper cognitive engagement, which may lead to more fragmented ...
IEEE

A Survey of Deep Transfer Learning in Automatic Modulation Classification

Abstract: Automatic modulation classification (AMC) is pivotal in both cooperative and non-cooperative communication systems. Despite achieving significant success in this field, deep learning (DL) is ...
Frontiers

A lightweight multi-deep learning framework for accurate diabetic retinopathy detection and multi-level severity identification

Accurate and timely detection of diabetic retinopathy (DR) is crucial for managing its progression and improving patient outcomes. However, developing algorithms to analyze complex fundus images ...
Scientific Research Publishing

Deep Learning for Neuroimaging-Based Brain Disorder Detection: Advancements and Future Perspectives ()

This review focuses on the recent advancements in neuroimaging enabled by deep learning techniques, specifically highlighting their applications in brain disorder detection and diagnosis. The ...