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Traffic Sign Detection Using a Cascade Method With Fast Feature Extraction and Saliency Test 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2017, 卷号: 18, 期号: 12, 页码: 3290-3302
作者:  Wang, Dongdong;  Hou, Xinwen;  Xu, Jiawei;  Yue, Shigang;  Liu, Cheng-Lin;  Cheng-Lin Liu
Adobe PDF(2774Kb)  |  收藏  |  浏览/下载：508/158  |  提交时间：2018/01/05
Traffic Sign Detection  Cascade System  Fast Feature Extraction  Saliency Test  
Traffic Sign Recognition Using a Multi-Task Convolutional Neural Network 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2018, 卷号: 19, 期号: 4, 页码: 1100-1111
作者:  Luo, Hengliang;  Yang, Yi;  Tong, Bei;  Wu, Fuchao;  Fan, Bin
浏览  |  Adobe PDF(4943Kb)  |  收藏  |  浏览/下载：803/374  |  提交时间：2018/01/04
Traffic Sign Detection  Traffic Sign Classification  Convolutional Neural Network  Multi-task Learning  
Towards Real-Time Traffic Sign Detection and Classification 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 卷号: 17, 期号: 7, 页码: 2022-2031
作者:  Yang, Yi;  Luo, Hengliang;  Xu, Huarong;  Wu, Fuchao
浏览  |  Adobe PDF(3538Kb)  |  收藏  |  浏览/下载：990/383  |  提交时间：2016/10/20
Traffic Sign Detection  Traffic Sign Recognition  Real-time  Color Probability Model  
Visual Tracking Based on Dynamic Coupled Conditional Random Field Model 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 卷号: 17, 期号: 3, 页码: 822-833
作者:  Liu, Yuqiang;  Wang, Kunfeng;  Shen, Dayong;  Wang, Kunfeng(王坤峰)
浏览  |  Adobe PDF(1757Kb)  |  收藏  |  浏览/下载：393/125  |  提交时间：2016/04/06
Coupled Conditional Random Field  Dynamic Models  Visual Tracking  Region-level Tracking  Spatiotemporal Context  
Rear-View Vehicle Detection and Tracking by Combining Multiple Parts for Complex Urban Surveillance 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2014, 卷号: 15, 期号: 2, 页码: 597-606
作者:  Tian, Bin;  Li, Ye;  Li, Bo;  Wen, Ding;  Bin Tian
浏览  |  Adobe PDF(1776Kb)  |  收藏  |  浏览/下载：387/157  |  提交时间：2015/08/12
Kalman Filter (Kf)  Markov Random Field (Mrf)  Part-based Object Detection  Tracking  Vehicle Detection