Deep learning is a subdiscipline of artificial intelligence that uses a machine learning
technique called artificial neural networks to extract patterns and make predictions from …

Deep learning has emerged as a potential tool for crop yield prediction, allowing the model
to automatically extract features and learn from the datasets. Meanwhile, smart farming …

Advancements in structural health monitoring (SHM) techniques have spiked in the past few
decades due to the rapid evolution of novel sensing and data transfer technologies. This …

Multimodal biomedical data fusion plays a pivotal role in distilling comprehensible and
actionable insights by seamlessly integrating disparate biomedical data from multiple …

Multimodal Artificial Intelligence (Multimodal AI), in general, involves various types of data
(eg, images, texts, or data collected from different sensors), feature engineering (eg …

In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …

Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …

Semantic communications focus on the transmission of semantic features. In this letter, we
consider a task-oriented multi-user semantic communication system for multimodal data …

Video summarization technologies aim to create a concise and complete synopsis by
selecting the most informative parts of the video content. Several approaches have been …

In recent years, deep learning algorithms have rapidly revolutionized artificial intelligence,
particularly machine learning, enabling researchers and practitioners to extend previously …