Event Detection

Event detection focuses on automatically identifying and classifying events within various data streams, such as audio, text, time series, and sensor data, aiming for accurate and timely event localization and categorization. Current research emphasizes improving model efficiency and robustness, exploring architectures like transformers and recurrent spiking neural networks, and addressing challenges like class imbalance, rare events, and catastrophic forgetting in continual learning scenarios. This field is crucial for applications ranging from environmental monitoring and healthcare to financial analysis and autonomous systems, driving advancements in both model design and data processing techniques.