The paper presents a training-free ANN-to-SNN conversion framework using layer-wise adaptive firing patterns, sensitivity-based spike compression, and entropy-based early exit to cut energy and latency while maintaining accuracy.
In 2009 IEEE Conference on Computer Vision and Pattern Recognition, 248–255
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Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Network
The paper presents a training-free ANN-to-SNN conversion framework using layer-wise adaptive firing patterns, sensitivity-based spike compression, and entropy-based early exit to cut energy and latency while maintaining accuracy.