0000000001174613

AUTHOR

Tushar Chauhan

showing 1 related works from this author

Event-Based Trajectory Prediction Using Spiking Neural Networks

2021

International audience; In recent years, event-based sensors have been combined with spiking neural networks (SNNs) to create a new generation of bio-inspired artificial vision systems. These systems can process spatio-temporal data in real time, and are highly energy efficient. In this study, we used a new hybrid event-based camera in conjunction with a multi-layer spiking neural network trained with a spike-timing-dependent plasticity learning rule. We showed that neurons learn from repeated and correlated spatio-temporal patterns in an unsupervised way and become selective to motion features, such as direction and speed. This motion selectivity can then be used to predict ball trajectory…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]PolynomialComputer scienceNeuroscience (miscellaneous)Neurosciences. Biological psychiatry. Neuropsychiatry02 engineering and technologyunsupervised learningSNN[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]STDP03 medical and health sciencesCellular and Molecular Neuroscience0302 clinical medicineLearning rule0202 electrical engineering electronic engineering information engineeringEvent (probability theory)Original ResearchSpiking neural networkQuantitative Biology::Neurons and Cognitionmotion selectivitybusiness.industry[SCCO.NEUR]Cognitive science/Neuroscience[SCCO.NEUR] Cognitive science/NeuroscienceProcess (computing)Pattern recognitionspiking cameraTrajectoryball trajectory predictionUnsupervised learning020201 artificial intelligence & image processingArtificial intelligencebusiness030217 neurology & neurosurgeryEfficient energy useNeuroscienceRC321-571Frontiers in Computational Neuroscience
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