semantic_scholarProceedings of the International Conference on Neuromorphic Systems2026-08-04
Challenging the Spatiotemporal Processing of Neuromorphic Models through a Temporally-Rich Event-Based Dataset
J. Seekings, Peyton S. Chandarana, Arshia Eslami, Ramtin Zand
TL;DR: The research rigorously investigates how neuromorphic architectures encode and integrate temporal information by conducting a comprehensive ablation study using a hybrid network, and demonstrates that shallow neuromorphic integration effectively maximizes the gains from temporal integration while mitigating the information loss inherent in binary spike quantization.
While neuromorphic systems offer a promising path for processing dynamic, event-based data, current benchmarks often fail to isolate the specific impact of temporal integration on model performance. To address this, our research rigorously investigates how neuromorphic architectu…