TeamTTA: Efficient Multi-Device Collaboration for Open-Set Test-Time Adaptation via Cloud Integration
Zhijun Li (lizhijun_os@hit.edu.cn)
Deep neural networks (DNNs) deployed on edge devices often suffer from severe performance degradation when exposed to dynamic and continually shifting environments. Test-time adaptation (TTA) has emerged as a promising solution by updating models online with incoming test data. However, edge deployment poses unique challenges: limited computational resources, latency caused by adaptation delays, and knowledge isolation across devices. The situation becomes even more complex in open-world scenari