When Sensing Varies with Contexts: Context-as-Transform for Tactile Few-Shot Class-Incremental Learning

1. 1Decompose the acquisition context into transform components
2. 2Learn a context-aware transformation to adapt the model to new contexts
3. 3Apply the transformation to the few-shot learning model to improve performance
4. 4Evaluate the model on various tactile sensing tasks with different acquisition contexts

Machine learning researchers and engineers working on few-shot learning and tactile sensing applications can benefit from this approach to improve model performance in diverse contexts

💡 Adapting to varying acquisition contexts is crucial for improving few-shot class-incremental learning performance in tactile sensing applications

🤖 Context-as-Transform FSCIL (CaT-FSCIL) adapts to varying acquisition contexts in tactile sensing #FewShotLearning #TactileSensing