Name
Title | ||
|---|---|---|
Variable weight algorithm for convolutional neural networks and its applications to classification of seizure phases and types |
Abstract | ||
|---|---|---|
•Convolutional Neural Networks can be improved in terms of the classification performance and robustness by using variable weight structures.•Analysis of different data processing methods, models’ robustness and statistical properties.•Comparative analysis of variable weight convolutional neural networks and other widely used machine learning techniques.•Medical applications to the classification of seizure phases and types. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.patcog.2021.108226 | Pattern Recognition |
Keywords | DocType | Volume |
Variable weight convolutional neural networks,Machine learning,Seizure phase classification,Seizure type classification | Journal | 121 |
Issue | ISSN | Citations |
1 | 0031-3203 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guangyu Jia | 1 | 15 | 3.97 |
| H. K. Lam | 2 | 3618 | 193.15 |
| Kaspar Althoefer | 3 | 847 | 112.87 |