文章基本信息

标题：Image Recognition Using Machine Learning with the Aid of MLR
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作者：Meherunnesa Tania ; Diba Afroze ; Jesmin Akhter 等
期刊名称：International Journal of Image, Graphics and Signal Processing
印刷版ISSN：2074-9074
电子版ISSN：2074-9082
出版年度：2021
卷号：13
期号：6
页码：12-22
DOI：10.5815/ijigsp.2021.06.02
语种：English
出版社：MECS Publisher
摘要：In this paper, we use three machine learning techniques: Linear Discriminant Analysis (LDA) along different Eigen vectors of an image, Fuzzy Inference System (FIS) and Fuzzy c-mean clustering (FCM) to recognize objects and human face. Again, Fuzzy c-mean clustering is combined with multiple linear regression (MLR) to reduce the four-dimensional variable into two dimensional variables to get the influence of all variables on the scatterplot. To keep the outlier within narrow range, the MLR is again applied in logistic regression. Individual method is found suitable for particular type of object recognition but does not reveal standard range of recognition for all types of objects. For example, LDA along Eigen vector provides high accuracy of detection for human face recognition but very poor performance is found against discrete objects like chair, butterfly etc. The FCM and FIS are found to provide moderate result in all kinds of object detection but combination of three methods of the paper provide expected result with low process time compared to deep leaning neural network.
关键词：Logistic regression;Eigen decomposition;objective function;scatterplot and entropy based combined algorithm