EZhouNet: A framework based on graph neural network and anchor interval for the respiratory sound event detection

This work proposes a graph neural network-based framework with anchor intervals, capable of handling variable-length audio and providing more precise temporal localization for abnormal respiratory sound events, and improves both the flexibility and applicability of respiratory sound detection.