Work place: Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh
E-mail: da.bony1971@gmail.com
Website:
Research Interests: Data Structures and Algorithms, Natural Language Processing, Computational Learning Theory
Biography
Diba Afroze has completed her B.Sc. in Computer Science and Engineering from Jahangirnagar University, Dhaka, Bangladesh in 2019. Currently, she is pursuing her M.Sc. in Computer Science and Engineering from the same institution. She is working in the area of Machine Learning. Her expanded Research interest is Deep Learning, Natural Language Processing and Data Science.
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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