Lu Cao

Multi-Metric Prototypical Networks for Few-Shot Class-Incremental Learning

Few-shot class-incremental learning (FSCIL) requires a model to absorb new visual classes from a handful of labeled examples while preserving decisions for previously seen classes. Prototype insertion is attractive because it avoids incremental optimization, yet a single embedding geometry can make few-shot prototypes...

OSGS: A Framework for Online Scheduling of Satellite-Ground Collaborative Inference With Space Edge Computing