Name
Abstract | ||
|---|---|---|
•25 techniques for reshaping inputs for convolutional neural networks.•Some uncommon methods along with common techniques for reshaping.•Tested on six different datasets of multiple domains.•Techniques applied on Inception-V3, ResNet 18, and DenseNet-121 architecture.•Statistics about relative convergence, accuracy, agreement and chi-square test. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.patcog.2019.04.009 | Pattern Recognition |
Keywords | Field | DocType |
Deep learning,Convolutional neural network,Reshaping,Resizing,Input size | Convergence (routing),Residual,Convolutional neural network,Interpolation,Data acquisition,Artificial intelligence,Test data,Mirroring,Artificial neural network,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
93 | 1 | 0031-3203 |
Citations | PageRank | References |
2 | 0.42 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Swarnendu Ghosh | 1 | 20 | 5.37 |
| Nibaran Das | 2 | 391 | 40.72 |
| Mita Nasipuri | 3 | 725 | 107.01 |