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Mr. Mohammad Aminul Islam
Mr. Mohammad Aminul Islam

Assistant Professor Contact No : +8801812078605
Department of Computer Science and Mathematics Email : amin@bau.edu.bd
Faculty of Agricultural Engineering & Technology ResearchGate Google Scholar
Research Interest:   Cognitive Science Image Processing Computer Vision Deep Learning BioInformatics
BSc (Engg.)    - 2013
University of Chittagong
SSC    - 2006
Chittagong Municipal Model High School
MS    - 2019
Bangladesh Agricultural University, Mymensingh
HSC    - 2008
B.A.F. Shaheen College, Chittagong
Total Number:  4
  • "Evaluation of Paddy Seed Germination using Convolutional Neural Network", MS Thesis.

    Details: In this research, we proposed a new method for automatic detection of germinative paddy seeds. The method is divided into three phases: individual paddy seeds segmentation, image normalization, and classification of germinative seeds. In the paddy seeds segmentation, we used different image processing techniques like grayscale conversion, image enhancement, binarization, and morphological analysis. In image normalization, we kept fixed frame size and also maintained the angle between the major axis of the seed and frame to zero. In the classification phase, the germinative paddy seed is recognized by using the Convolutional Neural Networks (CNN).

  • Ensuring Automated Security in Close Water (Pond) Fish Cultivation.

Details: In our study, we proposed a novel technique to detect and supervise illegal fishing by using automatic video surveillance technique. This technique aims at detecting the presence of abandoned objects in a protected fisheries area and at automatically performing online semantic video segmentation in order to facilitate the human operator’s task of retrieving the cause of an alarm. This task is performed by operating image segmentation based on temporal rank-order filtering followed by classification using convolutional neural network (CNN) in order to reduce false alarms. In our system, the key frame is the one whether an object like human with or without fishhook or net is moving in protected fisheries area. We used image processing technique for detecting the foreground object and deep learning for classification of moving object

  • Automatic Disease Identification System from Paddy Leaf Images Using K-Means Clustering and Convolutional Neural Network

Details: We try to implement a new method called Automatic Disease Identification System (ADIS) to detect and classify paddy diseases using paddy leaf images. The method is divided into two phases, namely, detection of paddy diseases and classification of paddy diseases. In the disease detection phase, the disease affected portion of the paddy leaf is detected using the existing K-Means Clustering, edge detection, and morphological operations. In disease classification phase, the type of paddy disease is recognized by using the Convolutional Neural Networks (CNN).

  • Automatic paddy seed variety identification using Haralick texture features.

Details: This research is aimed at developing an automated system to identify paddy varieties by using multiple heterogeneous features extracted exploiting external, physical and textural properties. The external and physical features are extracted using the color and physical properties of paddy seed while the textural features are estimated by Haralick technique. These features are utilized to train feed forward neural network (FNN) to predict the paddy variety.

Total Number:  1

1. National Mobile  application  Development  Awareness &  Capacity Building  Program

Topic: Android  Application  Development

Location: CUET

DUration: 5 days


No service information available..
Total Number:  4
  1. Jaionto Karmokar, Mohammad Aminul Islam, Md. Rakib Hassan, and M.M. Billah. "Impact of seasonal climatic variability on rice yield in Bangladesh", Journal of Agrometeorology 22 (2), 165-171Impact Factor:0.133.
  2. Mohammad Aminul Islam, Md. Sayeed Iftekhar Yousuf, M. M. Billah. “Automatic Plant Detection using HOG And LBP Features with SVM.” International Journal of Computer (IJC), [S.l.], v. 33, n. 1, p. 26-38, apr. 2019. ISSN 2307-4523.
  3. Golam Rabbani, Mohammad Aminul Islam, Muhammad Anwarul Azim, Mohammad Khairul Islam, and Md Mostafizur Rahman. "Bangladeshi License Plate Detection and Recognition with Morphological Operation and Convolution Neural Network." In 2018 21st International Conference of Computer and Information Technology (ICCIT), pp. 1-5. IEEE, 2018.
  4. M .M. Billah, M.A. Islam, J. Karmokar, “Purity Measurement of Lentil using ANN for Safe Food.” Bangladesh Journal of Agricultural Engineering, Vol. 28 (1 & 2) 33-42:2017, ISSN 1015-4426.
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No patent information available..
Title Institution Subject Receipt Date
Prime Minister Gold Medal UGC Gold Medal 25/2/2018
No professional affiliation information available..