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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 Trump Says He Is ...
Sports Illustrated

Bryce Young, Malik Washington And 4 More Deep Sleepers To Consider Starting In Week 5

This week, many fantasy owners will have to look deep into their bench to find players to start. Players that they might not usually put in their lineup, but with injuries and bye weeks piling up, we ...
eLife

Identification of type 2 diabetes- and obesity-associated human β-cells using deep transfer learning

This is a useful study that applies deep transfer learning to assign patient-level disease attributes to single cells of T2D and non-diabetic patients, including obese patients. This analysis ...
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 ...
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 ...
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 ...
Frontiers

AppleLeafNet: a lightweight and efficient deep learning framework for diagnosing apple leaf diseases

Accurately identifying apple diseases is essential to control their spread and support the industry. Timely and precise detection is crucial for managing the spread of diseases, thereby improving the ...
IEEE

A Transfer Learning Framework for Deep Multi-Agent Reinforcement Learning

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 ...
Frontiers

Tea leaf disease and insect identification based on improved MobileNetV3

Accurate detection of tea leaf diseases and insects is crucial for their scientific and effective prevention and control, essential for ensuring the quality and yield of tea. Traditional methods for ...