Abu Sayed Md. Mostafizur Rahaman

Work place: Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh

E-mail: sairoelamertet23@gmail.com


Research Interests: Network Security, Information Security, Systems Architecture, Embedded System, Computer systems and computational processes, World Wide Web, Data Structures and Algorithms


Abu Sayed Md. Mostafizur Rahaman has received PhD degree in 2014 from Department of Computer Science and Engineering of Jahangirnagar University, Savar, Dhaka, Bangladesh and obtained M.Sc. degree from Stuttgart University at Stuttgart, Germany in Information Technology (INFOTECH) in the branch of Embedded System Engineering in 2009. He received his B.Sc. degree in Electronics and Computer Science, from Jahangirnagar University, Savar, Dhaka, Bangladesh in 2003. Since 2004, he is a faculty member having current Designation "Professor" in the Department of Computer Science and Engineering of Jahangirnagar University, Savar, Dhaka, Bangladesh. During his graduation, he worked at BOSCH (biggest automobile company in Germany ) as Trainee engineer (Industrial internship) as part of his graduate degree in embedded Systems. Currently his research focuses on IoT, Digital Forensics, Ethical Hacking, Web Security, Embedded Systems and S/W Systems.

Author Articles
Image Recognition Using Machine Learning with the Aid of MLR

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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