Name
Title | ||
|---|---|---|
Visual Pattern Recognition Using Enhanced Visual Features and PSD-Based Learning Rule. |
Abstract | ||
|---|---|---|
This paper proposes a feedforward visual pattern recognition model based on a spiking neural network (SNN). The proposed model mainly includes four functional layers: 1) feature extraction; 2) encoding; 3) learning; and 4) readout. A modified HMAX model is first presented to extract features from external stimuli. In order to reduce the computational cost, we simplify the S1 layer using a single G... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCDS.2017.2769166 | IEEE Transactions on Cognitive and Developmental Systems |
Keywords | Field | DocType |
IEEE transactions | Caltech 101,MNIST database,Pattern recognition,Computer science,Robustness (computer science),Gabor filter,Feature extraction,Learning rule,Artificial intelligence,Spiking neural network,Encoding (memory) | Journal |
Volume | Issue | ISSN |
10 | 2 | 2379-8920 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||