Work place: Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh
E-mail: taniajucse25@gmail.com
Website:
Research Interests: Robotics, Neural Networks, Computational Learning Theory, Artificial Intelligence, Computer systems and computational processes
Biography
Meherunnesa Tania has completed her B.Sc. Engineering in Computer Science and Engineering from Jahangirnagar University and pursuing her M.Sc. from the same University. Her research interests are Machine Learning, Robotics and Artificial Intelligence, Neural Network etc
By Meherunnesa Tania Diba Afroze Jesmin Akhter Abu Sayed Md. Mostafizur Rahaman Md. Imdadul Islam
DOI: https://doi.org/10.5815/ijigsp.2021.06.02, Pub. Date: 8 Dec. 2021
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.
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