#layer-wise-relevance News & Analysis

An accuracy-aware extension to LRP-based pruning for CNNs to prevent cascading accuracy degradation in data-scarce transfer learning

Researchers propose an accuracy-aware pruning mechanism for CNNs that improves upon existing Layer-wise Relevance Propagation (LRP) methods to reduce model size without degrading performance in transfer learning scenarios with limited data. The approach dynamically adjusts pruning rates using harmonic mean of class accuracy, achieving 15% improvement in compression efficiency while maintaining task-specific accuracy.