Name
Abstract | ||
|---|---|---|
•A novel approach for 3D object recognition is proposed.•The proposal relies on deep learning pre-trained models for image annotation.•Mixing 2D and 3D techniques for processing data improve recognition capabilities.•Proposal can get over errors introduced by the labeling tool.•Experimental results prove the effectiveness of the proposed procedure. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.asoc.2018.02.005 | Applied Soft Computing |
Keywords | Field | DocType |
Object recognition,Deep learning,Object labeling,Machine learning | Spatial analysis,Convolutional neural network,Robustness (computer science),Artificial intelligence,Deep learning,Merge (version control),Classifier (linguistics),Mathematics,Machine learning,Cognitive neuroscience of visual object recognition | Journal |
Volume | ISSN | Citations |
65 | 1568-4946 | 3 |
PageRank | References | Authors |
0.43 | 21 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Carlos Rangel | 1 | 24 | 3.11 |
| Jesus Martínez-Gómez | 2 | 115 | 11.09 |
| Cristina Romero-González | 3 | 4 | 1.16 |
| Ismael García-varea | 4 | 275 | 36.16 |
| Miguel Cazorla | 5 | 325 | 44.17 |