Name
Title | ||
|---|---|---|
A New Approach to Track Multiple Vehicles With the Combination of Robust Detection and Two Classifiers. |
Abstract | ||
|---|---|---|
It plays an important role to accurately track multiple vehicles in intelligent transportation, especially in intelligent vehicles. Due to complicated traffic environments it is difficult to track multiple vehicles accurately and robustly, especially when there are occlusions among vehicles. To alleviate these problems, a new approach is proposed to track multiple vehicles with the combination of ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TITS.2017.2756989 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | Field | DocType |
Support vector machines,Robustness,Interference,Object detection,Optical imaging,Feature extraction,Adaptive optics | Object detection,Computer vision,Convolutional neural network,Local binary patterns,Support vector machine,Feature extraction,Robustness (computer science),Artificial intelligence,Engineering,Classifier (linguistics),Life length | Journal |
Volume | Issue | ISSN |
19 | 1 | 1524-9050 |
Citations | PageRank | References |
5 | 0.41 | 33 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weidong Min | 1 | 40 | 9.44 |
| Mengdan Fan | 2 | 5 | 0.75 |
| Xiaoguang Guo | 3 | 5 | 0.41 |
| Qing Han | 4 | 5 | 1.42 |