Name
Title | ||
|---|---|---|
Improving Performance of Devanagari Script Input-Based P300 Speller Using Deep Learning. |
Abstract | ||
|---|---|---|
The performance of an existing Devanagari script (DS) input-based P300 speller with conventional machine learning techniques suffers from low information transfer rate (ITR). This occurs due to its required large size of display, i.e., 8 × 8 row-column (RC) paradigm which exhibits issues like crowding effect, adjacency, fatigue, task difficulty, and required large number of trials for character re... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TBME.2018.2875024 | IEEE Transactions on Biomedical Engineering |
Keywords | Field | DocType |
Machine learning,Electroencephalography,Support vector machines,Machine learning algorithms,Training,Brain modeling,Data acquisition | Computer vision,Devanagari,Autoencoder,Normalization (statistics),Information transfer,Convolutional neural network,Computer science,Support vector machine,Speech recognition,Artificial intelligence,Deep learning,Overfitting | Journal |
Volume | Issue | ISSN |
66 | 11 | 0018-9294 |
Citations | PageRank | References |
4 | 0.37 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ghanahshyam B. Kshirsagar | 1 | 6 | 1.42 |
| Narendra D. Londhe | 2 | 98 | 13.85 |