Name
Abstract | ||
|---|---|---|
We address the vehicle detection and classification problems using Deep Neural Networks (DNNs) approaches. Here we answer to questions that are specific to our application including how to utilize DNN for vehicle detection, what features are useful for vehicle classification, and how to extend a model trained on a limited size dataset, to the cases of extreme lighting condition. Answering these questions we propose our approach that outperforms state-of-the-art methods, and achieves promising results on image with extreme lighting conditions. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICDSP.2016.7868561 | 2016 IEEE International Conference on Digital Signal Processing (DSP) |
Keywords | Field | DocType |
Vehicle Classification,Deep Neural Network | Pattern recognition,Computer science,Image based,Vehicle detection,Artificial intelligence,Artificial neural network,Machine learning,Deep neural networks | Conference |
ISBN | Citations | PageRank |
978-1-5090-4166-4 | 3 | 0.49 |
References | Authors | |
13 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yiren Zhou | 1 | 18 | 2.79 |
| Hossein Nejati | 2 | 32 | 5.29 |
| Thanh-Toan Do | 3 | 173 | 24.22 |
| Ngai-Man Cheung | 4 | 750 | 67.36 |
| Lynette Cheah | 5 | 4 | 1.17 |