Name
Title | ||
|---|---|---|
Learning Sparse Feature Representations using Probabilistic Quadtrees and Deep Belief Nets |
Abstract | ||
|---|---|---|
Learning sparse feature representations is a useful instrument for solving an unsupervised learning problem. In this paper, we present three labeled handwritten digit datasets, collectively called n-MNIST by adding noise to the MNIST dataset, and three labeled datasets formed by adding noise to the offline Bangla numeral database. Then we propose a novel framework for the classification of handwritten digits that learns sparse representations using probabilistic quadtrees and Deep Belief Nets. On the MNIST, n-MNIST and noisy Bangla datasets, our framework shows promising results and outperforms traditional Deep Belief Networks. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s11063-016-9556-4 | Neural Processing Letters |
Keywords | Field | DocType |
Deep neural networks,Handwritten digit classification,Probabilistic quadtrees,Deep belief networks,Sparse feature representation | Deep belief nets,MNIST database,Pattern recognition,Computer science,Deep belief network,Bengali,Unsupervised learning,Artificial intelligence,Probabilistic logic,Artificial neural network,Numeral system,Machine learning | Journal |
Volume | Issue | ISSN |
abs/1509.03413 | 3 | 1370-4621 |
Citations | PageRank | References |
7 | 0.67 | 10 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Saikat Basu | 1 | 85 | 7.05 |
| Manohar Karki | 2 | 52 | 4.12 |
| Sangram Ganguly | 3 | 136 | 20.73 |
| Robert DiBiano | 4 | 54 | 4.79 |
| supratik mukhopadhyay | 5 | 267 | 39.44 |
| Ramakrishna R. Nemani | 6 | 455 | 91.96 |