Name
Abstract | ||
|---|---|---|
While most deep learning architectures are built on convolution, alternative foundations such as morphology are being explored for purposes such as interpretability and its connection to the analysis and processing of geometric structures. The morphological hit-or-miss operation has the advantage that it considers both foreground information and background information when evaluating the target sh... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TNNLS.2020.3025723 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | DocType | Volume |
Transforms,Convolution,Shape,Morphology,Artificial neural networks,Gray-scale,Machine learning | Journal | 32 |
Issue | ISSN | Citations |
11 | 2162-237X | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| muhammad aminul islam | 1 | 14 | 5.66 |
| Bryce Murray | 2 | 0 | 1.35 |
| Andrew Buck | 3 | 0 | 0.34 |
| Derek T. Anderson | 4 | 150 | 25.17 |
| Grant J. Scott | 5 | 214 | 22.19 |
| Mihail Popescu | 6 | 469 | 48.76 |
| James M. Keller | 7 | 3201 | 436.69 |