Ponencia
Live demonstration: Hardware implementation of convolutional STDP for on-line visual feature learning
Autor/es | Yousefzadeh, Amirreza
Masquelier, T. Serrano Gotarredona, María Teresa Linares Barranco, Bernabé |
Departamento | Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores |
Fecha de publicación | 2017 |
Fecha de depósito | 2020-07-08 |
Publicado en |
|
ISBN/ISSN | 2379-447X |
Resumen | We present live demonstration of a hardware that can learn visual features on-line and in real-time during presentation of objects. Input Spikes are coming from a bio-inspired silicon retina or Dynamic Vision Sensor (DVS) ... We present live demonstration of a hardware that can learn visual features on-line and in real-time during presentation of objects. Input Spikes are coming from a bio-inspired silicon retina or Dynamic Vision Sensor (DVS) and are processed in a Spiking Convolutional Neural Network (SCNN) that is equipped with a Spike Timing Dependent Plasticity (STDP) learning rule implemented on FPGA. |
Cita | Yousefzadeh, A., Masquelier, T., Serrano Gotarredona, M.T. y Linares Barranco, B. (2017). Live demonstration: Hardware implementation of convolutional STDP for on-line visual feature learning. En 2017ISCAS. IEEE International Symposium on Circuits and Systems Baltimore (USA): IEEE. Institute of Electrical and Electronics Engineers. |
Ficheros | Tamaño | Formato | Ver | Descripción |
---|---|---|---|---|
linares-barranco-pnencia_balti ... | 3.990Mb | [PDF] | Ver/ | |