The monthly PGRs Research Presentations was held on Wed. 10th Feb., 2pm, Room MC3108.

This session we had the following presentations:

Title: Event-based Continuous STDP Learning using HMAX Model for Visual Pattern Recognition.
 By: Daqi Liu

Abstract: Ventral stream within the visual cortex plays an important role in form recognition and object representation. Understanding and modeling the processing mechanism of the ventral stream is quite significant and necessary for visual pattern recognition application. In our research, an event-based continuous spike timing dependent plasticity (STDP) learning method (ECS) using HMAX model for visual pattern recognition has been proposed. Through the proposed spiking encoding scheme, the spatiotemporal spiking pattern would be generated from the high-level features extracted from HMAX model and such spatiotemporal information conveys unique and distinguish selectivity to each input visual stimuli. The selectivity to the input visual stimuli will be emerged after the continuous learning using the proposed event-based STDP method. By incorporating background neural noise and time jitter into the input visual stimuli of the proposed method while adding nothing into the classic SVM algorithm, cross-validated experimental results on MNSIT handwritten character database show that the proposed ECS method still achieves a better performance even in such harsh conditions.