Fusion Network

Fusion networks are artificial neural networks designed to integrate information from multiple data sources (modalities), such as images, text, and sensor readings, to improve the accuracy and robustness of various tasks. Current research focuses on developing novel fusion architectures, including those based on transformers, residual networks, and attention mechanisms, to optimize feature extraction and integration strategies for specific applications. These advancements are significantly impacting fields like medical image analysis, autonomous driving, and multimedia forensics by enabling more accurate and reliable predictions and classifications than single-modality approaches.