Prediction Error-based Classification (PEC) introduces a novel approach for class-incremental learning by utilizing prediction errors to generate class scores, outperforming other methods in single-pass-through-data scenarios.
Prediction Error-based Classification (PEC) offers a novel and efficient approach for class-incremental learning, outperforming other methods in single-pass-through-data scenarios.
Prediction Error-based Classification (PEC) offers a novel and efficient approach for class-incremental learning, outperforming other methods in single-pass-through-data scenarios.
PEC bietet eine effiziente Alternative für generative Klassifizierung in Class-Incremental Learning.