Abstract
A Recognition method of CD4 cell images and the principle of support vector machines are studied in this paper. The recognition method based on SVM is proposed to solve Microscopic image recognition of CD4 cell with a small sample size and less prior knowledge. An improved parallel grid search method is used to choose the parameters of OSU_SVM classifier, so the computation time is significantly reduced. Cross validation is employed to test the performance of SVM classification. With this new method, the recognition rate of CD4 cell image reaches to 95 % which higher than that of conventional methods. The tests show that the OSU_SVM approach is better than the conventional methods such as Fisher classifier, BP neural networks and LS-SVM.
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Liu, Y. (2013). Recognition of CD4 Cell Images Based on SVM with an Improved Parameter. In: Wong, W.E., Ma, T. (eds) Emerging Technologies for Information Systems, Computing, and Management. Lecture Notes in Electrical Engineering, vol 236. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7010-6_62
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DOI: https://doi.org/10.1007/978-1-4614-7010-6_62
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