TP7b.2

Reading Events Hierarchically to Reduce Latency

Leo Liu, Kwabena Boahen, Stanford University, United States
Session:
TP7b: Neuromorphic Computing: Algorithms and Embedded Hardware Architectures Lecture
Track:
Architectures and Implementation
Location:
Oak Shelter
Presentation Time:
Tue, 29 Oct, 15:55 - 16:20 PT (UTC -8)
Session Chair:
Federico Corradi, TU Eindhoven
Presentation
Discussion
Resources
No resources available.
Session TP7b
TP7b.1: Event-driven frequency decomposition with spiking phase-locked loops
Hugh Greatorex, Elisabetta Chicca, University of Groningen, Netherlands
TP7b.2: Reading Events Hierarchically to Reduce Latency
Leo Liu, Kwabena Boahen, Stanford University, United States
TP7b.3: QUANTISENC++: A Fully-Configurable Many-Core Neuromorphic Hardware
Shadi Matinizadeh, Arghavan Mohammadhassani, M. L Varshika, Sarah Johari, Anup Das, Drexel University, United States
TP7b.4: Waves and symbols in neuromorphic hardware: from analog signal processing to digital computing on the same computational substrate
Giacomo Indiveri, University of Zurich, ETH Zurich, Switzerland
TP7b.5: SpikeVision: A Fully Spiking Neural Network Transformer-Inspired Model for Dynamic Vision Sensors
Zhanbo Shen, Federico Corradi, Eindhoven University of Technology, Netherlands
Contacts