Department of Computer Science & Engineering (CSE)
Umme
Sara is a faculty of computer science and engineering department at National
Institute of Textile Engineering & Research (NITER). At now, she is serving
as head of the department of computer science and engineering.
She
holds her bachelor and master's degree from the department of CSE of
Jahangirnagar University in 2014 and 2016 respectively. Currently she is an ongoing
PhD researcher at the same institution. Her research area includes computer
vision system, digital image processing, machine learning and data science.
Sara
began working as a lecturer in this institution in October 2015.Before joining
at NITER, she served as a lecturer at Gono University, Savar, Dhaka. She has also been the Superintendent
of NITER Female Hostel's since 2020. Umme Sara is currently the member of
NITER Coordination & Development Committee.
Degree Name | Group/Major Subject | Board/Institute | Country | Passing Year |
---|---|---|---|---|
PhD | CSE (Image Feature Classification and Ranking) | Jahangirnagar University | Bangladesh | On Going |
Jahangirnagar University | CSE (Image Processing) | Jahangirnagar University | Bangladesh | 2016 |
Title | Organization | Location | From Date | To Date |
---|---|---|---|---|
Lecturer | Gono Bishwabidyalaya | Savar,Dhaka | 03/13/2014 | 10/12/2015 |
Lecturer | National Institute of Textile Engineering and Research (NITER) | Nayarhat,Savar,Dhaka | 10/13/2015 | 03/02/2020 |
Assistant Professor | National Institute of Textile Engineering and Research (NITER) | Nayarhat,Savar,Dhaka | 03/03/2020 | Continue |
Head of the Dept. | National Institute of Textile Engineering and Research (NITER) | Nayarhat,Savar,Dhaka | 09/28/2021 | Continue |
Hostel Superintendant | National Institute of Textile Engineering and Research (NITER) | Nayarhat,Savar,Dhaka | 03/12/2020 | Continue |
Subject | Description | Research Interest (Goal, Target Indicator) |
---|---|---|
Automatic Disease Detection (Vegetables and Agricultural Crops) | Digital
image processing, Pattern Recognition, Feature Extraction Texture Analysis and
image quality analysis on vegetables and agricultural crops image data |
PhD program Curriculum |
Computer Vision System | Computer
Vision System to disease diagnosis and fault detection using machine learning and Deep Learning approach |
Current Research proposal Title-1 |
Pattern Recognition System | Using
Pattern Recognition and classification to extract features and ranking them to
diagnose successfully the diseases of vegetables and Agricultural |
Current Research proposal Title-2 |
Level of Study | Title | Supervisor | Co-Supervisor(s) | Name of Student(s) | Area of Research | Current Completion |
---|---|---|---|---|---|---|
No project/research supervision is found |
Subject | Project Name | Source of Fund | From Date | To Date | Collaboration |
---|---|---|---|---|---|
No project/research work is found |
SL | Invited Talk |
---|---|
No invited talk is found |
Collaboration & Membership Name | Type | Membership Year | Expire Year | |
---|---|---|---|---|
No Data Found |
Journal Article | |
---|---|
1 |
Image quality assessment through FSIM, SSIM, MSE and PSNR—a comparative study |
2 |
An extensive sunflower dataset representation for successful identification and classification of sunflower diseases |
3 |
VegNet: An organized dataset of cauliflower disease for a sustainable agro-based automation system |
4 |
SGBBA: An Efficient Method for Prediction System in Machine Learning using Imbalance Dataset |
5 |
DistB-SDoIndustry: Enhancing Security in Industry 4.0 Services based on Distributed Blockchain through Software Defined Networking-IoT Enabled Architecture |
6 |
A comprehensive guava leaves and fruits dataset for guava disease recognition |
7 |
On the Integration of Blockchain and SDN: Overview, Applications, and Future Perspectives |
8 |
Towards the development of an energy-efficient smart home through IoT |
Conference Proceedings | |
1 |
Utilization of Five-Distinct Dataset to Diagnose and Predict Heart Disease: A Machine Learning Approach |
2 |
A machine learning approach to detect the brain stroke disease |
Award Type | Title | Year | Country | Description |
---|---|---|---|---|
No Data Found |
Academic
Mail:
usara@niter.edu.bd ; headcse@niter.edu.bd
Contact:
+880-1882567003
Institute
– Faculty
Name
of the Department: Computer Science and Engineering
Position: Assistant
Professor and Head of the Department