Higher Coverage Rate

Higher coverage rate research focuses on improving the comprehensiveness and representativeness of data or model outputs across various domains. Current efforts involve developing novel algorithms and model architectures, such as those based on reinforcement learning, to optimize coverage while addressing issues like bias and computational efficiency. This research is significant because achieving higher coverage rates is crucial for improving the reliability and generalizability of results in diverse fields, ranging from urban mapping and machine learning to autonomous systems and network optimization. The ultimate goal is to ensure that models and analyses accurately reflect the underlying phenomena they aim to represent.