Transfer-learned SpikeYOLO achieves mAP 0.937/0.771 and HOTA 0.701/0.445 on KITTI and BDD100K for two-class automotive detection and tracking, competitive with conventional deep networks.
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A Review of the Integrate-and-fire Neuron Model: I. Homogeneous Synaptic Input,
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Efficient Perception in Automotive Detection and Tracking Using Neuromorphic Computing
Transfer-learned SpikeYOLO achieves mAP 0.937/0.771 and HOTA 0.701/0.445 on KITTI and BDD100K for two-class automotive detection and tracking, competitive with conventional deep networks.