Name
Title | ||
|---|---|---|
MCFF-CNN: Multiscale Comprehensive Feature Fusion Convolutional Neural Network for Vehicle Color Recognition Based on Residual Learning |
Abstract | ||
|---|---|---|
Automatic vehicle color recognition is very important for video surveillance, especially for intelligent transportation system. Currently, some approaches have been proposed. However, it is still very difficult to recognize the vehicle color correctly in the complex traffic scenes with constantly changing illuminations. To solve this problem, we propose a new network structure - Multiscale Comprehensive Feature Fusion Convolutional Neural Network (MCFF-CNN) based on residual learning for color feature extraction. First, we use MCFF-CNN network to extract the deep color features of the vehicles. Then, we employ support vector machine (SVM) classifier to obtain the final color recognition results. Based on the proposed approach, we have built a system for robust vehicle color recognition in practical traffic scenes. Extensive experimental results show our solution is effective. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.neucom.2018.02.111 | Neurocomputing |
Keywords | DocType | Volume |
Vehicle color recognition,Convolutional neural network,Residual learning,Video surveillance,Intelligent transportation system | Journal | 395 |
ISSN | Citations | PageRank |
0925-2312 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huiyuan Fu | 1 | 68 | 13.24 |
| Huadong Ma | 2 | 2020 | 179.93 |
| Gaoya Wang | 3 | 0 | 0.34 |
| Xiaomou Zhang | 4 | 0 | 0.34 |
| Yifan Zhang | 5 | 2 | 1.72 |