Event Classification

Event classification focuses on automatically assigning categories to events detected in various data streams, aiming for accurate and efficient identification. Current research emphasizes improving model robustness against noise and variations in data sources, exploring architectures like convolutional and transformer networks, graph neural networks, and hybrid quantum-classical models, often incorporating multimodal data fusion techniques. This field is crucial for applications ranging from environmental monitoring (acoustic event detection) and industrial process control (power system event identification) to high-energy physics and crisis management, driving advancements in both machine learning algorithms and data representation.