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Found 4 papers, 0 papers with code
Dynamic Training of Liquid State Machines
The experimental results showed that by using spike metrics and a range of weights, the desired output and the actual output of spiking neurons could be effectively optimised, leading to improved performance of SNNs.
NeuroHSMD: Neuromorphic Hybrid Spiking Motion Detector
Vertebrate retinas are highly-efficient in processing trivial visual tasks such as detecting moving objects, yet a complex challenges for modern computers.
HSMD: An object motion detection algorithm using a Hybrid Spiking Neural Network Architecture
The detection of moving objects is a trivial task performed by vertebrate retinas, yet a complex computer vision task.
LabelSens: Enabling Real-time Sensor Data Labelling at the point of Collection on Edge Computing
Labelling is an indispensable stage of data pre-processing that can be particularly challenging, especially when applied to single or multi-model real-time sensor data collection approaches.
