Co-active: an efficient selective relabeling model for resource constrained edge AI

Chenyu Hou, Kai Jiang, Tiantian Li, Meng Zhou, Jun Jiang

Abstract: With high-quality annotation data, edge AI has emerged as a pivotal technology in various domains. Unfortunately, due to sensor errors and discrepancies in data collection, datasets often suffer from noisy labels. Identifying and relabeling all the noisy data becomes imperative, but it’s labor-intensive and time-consuming. To ensure the robustness of resource-constrained edge AI models with noisy labels, in this paper, we propose an efficient selective relabeling method

External IDs:dblp:journals/winet/HouJLZJ25