Road-Sign Identification Using Ensemble Learning

@inproceedings{citeulike:2467508, abstract = {Ensemble learning that combines the decisions of multiple weak classifiers to from an output, has recently emerged as an effective identification method. This paper presents a road-sign identification system based upon the ensemble learning approach. The system identifies the regions of interest that are extracted from the scene into the road-sign groups that they belong to. A large road-sign image dataset is formed and used to train and test the system. Fifteen groups of road signs are chosen for identification. Five experiments are performed and the results are presented and discussed.}, author = {Kouzani, Abbas Z. }, booktitle = {Intelligent Vehicles Symposium, 2007 IEEE}, citeulike-article-id = {2467508}, doi = {10.1109/IVS.2007.4290154}, journal = {Intelligent Vehicles Symposium, 2007 IEEE}, keywords = {ensemble, recognition, sign}, pages = {438--443}, posted-at = {2008-03-04 19:52:03}, priority = {2}, title = {Road-Sign Identification Using Ensemble Learning}, url = {http://dx.doi.org/10.1109/IVS.2007.4290154}, year = {2007} }

TY - CONF ID - citeulike:2467508 L3 - citeulike-article-id:2467508 TI - Road-Sign Identification Using Ensemble Learning T2 - Intelligent Vehicles Symposium, 2007 IEEE JF - Intelligent Vehicles Symposium, 2007 IEEE SP - 438 EP - 443 N2 - Ensemble learning that combines the decisions of multiple weak classifiers to from an output, has recently emerged as an effective identification method. This paper presents a road-sign identification system based upon the ensemble learning approach. The system identifies the regions of interest that are extracted from the scene into the road-sign groups that they belong to. A large road-sign image dataset is formed and used to train and test the system. Fifteen groups of road signs are chosen for identification. Five experiments are performed and the results are presented and discussed. KW - ensemble KW - recognition KW - sign AU - Kouzani, Abbas PY - 2007/// UR - http://dx.doi.org/10.1109/IVS.2007.4290154 ER -