Multi-scale vehicle classification using different machine learning models
College
Gokongwei College of Engineering
Department/Unit
Manufacturing Engineering and Management
Document Type
Conference Proceeding
Source Title
2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2018
Publication Date
3-12-2019
Abstract
The focus of this paper is to explore multi-scale vehicle classification based on the histogram of oriented gradient features. Several literatures have used these features together with different classification models, however, there is a need to compare different models suited for vehicle classification application. In order to quantify the results a common dataset was used for the machine learning models: logistic regression, k-nearest neighbor, and support vector machine. However, since the classification of the support vector machine is based on the type of kernel (linear, polynomial, and Gaussian) used, additional tests were conducted. Thus, this study provides the following contributions: (1) comparison of machine learning models for vehicle classification; and (2) comparison of the best type of kernel function. © 2018 IEEE.
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Digitial Object Identifier (DOI)
10.1109/HNICEM.2018.8666378
Recommended Citation
Roxas, E. A., Vicerra, R. P., Gan Lim, L. A., Dela Cruz, J. C., Naguib, R. G., Dadios, E. P., & Bandala, A. A. (2019). Multi-scale vehicle classification using different machine learning models. 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2018 https://doi.org/10.1109/HNICEM.2018.8666378
Disciplines
Manufacturing | Mechanical Engineering
Keywords
Vehicles; Computer vision; Machine learning; Nearest neighbor analysis (Statistics); Kernel functions; Logistic regression analysis
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