Name
Abstract | ||
|---|---|---|
•It is a regression model based on 1D-CNN for predicting the relative location of CT scan images.•A public dataset in the UCI repository was used to evaluate the proposed model.•The accuracy and speed of the proposed model outperformed other machine learning-based methods by a large margin.•The performance of the proposed model on small datasets was also better than that of the KNN model. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.cmpb.2018.03.025 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
Convolutional neural networks,CT scan images,Relative location prediction | Computer vision,Feature vector,Spatial correlation,Normalization (statistics),Computer science,Convolutional neural network,Artificial intelligence,Overfitting,Shape context,Cross-validation,Approximation error | Journal |
Volume | ISSN | Citations |
160 | 0169-2607 | 0 |
PageRank | References | Authors |
0.34 | 12 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiajia Guo | 1 | 41 | 5.75 |
| Hongwei Du | 2 | 43 | 7.29 |
| Jianyue Zhu | 3 | 76 | 4.07 |
| Ting Yan | 4 | 0 | 0.34 |
| Bensheng Qiu | 5 | 11 | 6.59 |