Name
Title | ||
|---|---|---|
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy for Detection of Informative Frames. |
Abstract | ||
|---|---|---|
•Simplifying CNN and MLP structures to reduce the number of computational operations.•Achieving AUC-ROC greater than 0.97 for segmentation of bleeding regions in WCE.•Proposed structures could be selected for inside capsule implementation. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.bspc.2019.101565 | Biomedical Signal Processing and Control |
Keywords | Field | DocType |
Wireless capsule endoscopy,Neural network quantization,Neural network pruning,Hardware implementation | Computer vision,Wireless,Pattern recognition,Convolutional neural network,Segmentation,Artificial intelligence,Capsule endoscopy,Artificial neural network,Contextual image classification,Perceptron,Mathematics,Channel (digital image) | Journal |
Volume | ISSN | Citations |
53 | 1746-8094 | 1 |
PageRank | References | Authors |
0.36 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohsen Hajabdollahi | 1 | 4 | 4.81 |
| Reza Esfandiarpoor | 2 | 1 | 1.04 |
| P. Khadivi | 3 | 106 | 12.15 |
| S. M. R. Soroushmehr | 4 | 71 | 21.08 |
| Nader Karimi | 5 | 145 | 32.75 |
| Kayvan Najarian | 6 | 262 | 59.53 |
| Shadrokh Samavi | 7 | 233 | 38.99 |