Publication: Robust Learning and Recognition of Visual Patterns in Neuromorphic Electronic Agents
Robust Learning and Recognition of Visual Patterns in Neuromorphic Electronic Agents
Date
Date
Date
Citations
Liang, D., Kreiser, R., Nielsen, C., Qiao, N., Sandamirskaya, Y., & Indiveri, G. (2019, March 20). Robust Learning and Recognition of Visual Patterns in Neuromorphic Electronic Agents. 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), Hsinchu. https://doi.org/10.1109/aicas.2019.8771580
Abstract
Abstract
Abstract
Mixed-signal analog/digital neuromorphic circuits are characterized by ultra-low power consumption, real-time processing abilities, and low-latency response times. These features make them promising for robotic applications that require fast and power-efficient computing. However, the unavoidable variance inherently existing in the analog circuits makes it challenging to develop neural processing architectures able to perform complex computations robustly. In this paper, we present a spiking neural network architecture with spike-base
Metrics
Additional indexing
Creators (Authors)
- Liang, Dongchen
- Kreiser, Raphaela
- Nielsen, Carsten
- Qiao, Ning
- Sandamirskaya, Yulia
Event Title
Event Title
Event Title
Event Location
Event Location
Event Location
Event Country
Event Country
Event Country
Event Start Date
Event Start Date
Event Start Date
Event End Date
Event End Date
Event End Date
Publisher
Publisher
Publisher
Item Type
Item Type
Item Type
In collections
Language
Language
Language
Date available
Date available
Date available
ISBN or e-ISBN
ISBN or e-ISBN
ISBN or e-ISBN
OA Status
OA Status
OA Status
Free Access at
Free Access at
Free Access at
Publisher DOI
Metrics
Citations
Liang, D., Kreiser, R., Nielsen, C., Qiao, N., Sandamirskaya, Y., & Indiveri, G. (2019, March 20). Robust Learning and Recognition of Visual Patterns in Neuromorphic Electronic Agents. 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), Hsinchu. https://doi.org/10.1109/aicas.2019.8771580
