Title :
An Algorithm Based on Imbalance Samples for Vehicle Recognition
Author :
Wen, Xuezhi ; Zhao, Yingnan
Author_Institution :
Coll. of Comput. & Software, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
Abstract :
A vehicle recognition algorithm is proposed to solve imbalanced datasets in vehicle recognition based on SVM ensembles. Moreover, an improved Wavelet feature algorithm is also presented. Experimental results show that the presented method has high precision and recall. Furthermore, the system performance can also be improved by increasing learning and has better application.
Keywords :
feature extraction; learning (artificial intelligence); object recognition; support vector machines; vehicles; wavelet transforms; SVM ensembles; imbalance samples; imbalanced datasets; vehicle recognition; wavelet feature algorithm; Data mining; Educational institutions; Feature extraction; Information science; Neural networks; Pattern recognition; Software algorithms; Support vector machine classification; Support vector machines; Vehicle detection;
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
DOI :
10.1109/ICISE.2009.229
