Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter ...

1 Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia 2 Center of Excellence in Intelligent Engineering Systems (CEIES), King ...

MIAFEx is a Transformer-based extractor for medical images that refines the [CLS] token to produce robust features, improving results on small or imbalanced datasets and supporting feature selection ...

We break down the Encoder architecture in Transformers, layer by layer! If you've ever wondered how models like BERT and GPT process text, this is your ultimate guide. We look at the entire design of ...

Accurate short-to-subseasonal streamflow forecasts are becoming crucial for effective water management in an increasingly variable climate. However, streamflow forecast remains challenging over ...

We dive into Transformers in Deep Learning, a revolutionary architecture that powers today's cutting-edge models like GPT and BERT. We’ll break down the core concepts behind attention mechanisms, self ...

Abstract: The miniaturization of Inertial Measurement Units (IMUs) has expanded their use in various devices like smartphones and drones. Traditional attitude estimation methods lack robustness across ...

Introduction: Accurate wheat yield estimation is crucial for efficient crop management. This study introduces the Spatio–Temporal Fusion Mixture of Experts (STF-MoE) model, an innovative deep learning ...

Abstract: This study introduces an innovative deep learning framework, the Weber Cross Information Sharing Deep Learning Encoder-Decoder (WCISD-ED) model, designed for emotion recognition through ...