Real-time detection is a research area that focuses on developing algorithms and technologies for detecting events, objects, or patterns in real-time. This could include detecting anomalies, threats, or trends in data streams, images, videos, or sensor data. Real-time detection is often used in various applications such as surveillance, cybersecurity, financial fraud detection, and predictive maintenance. The goal of real-time detection is to quickly identify and respond to events as they occur, facilitating timely decision-making and action. Researchers in this area often work on developing efficient, scalable, and accurate detection algorithms that can handle large volumes of data in real-time.