Profile

Md. Faysal Ahamed

মোঃ ফয়সাল আহম্মেদ

Lecturer

Md. Faysal Ahamed, a diligent researcher from Bangladesh, has demonstrated an unrelenting dedication to education and creativity throughout his academic and professional career. He graduated from Rajshahi University of Engineering and Technology (RUET) with a Bachelor of Science degree in Electrical and Computer Engineering with a CGPA of 3.85 (Department 2nd) out of 4.00. He was awarded Student of The Year 2021, 2022. He is now studying for a Master of Science in Computer Science and Engineering at RUET. He has been a lecturer in the Department of Electrical and Computer Engineering at Rajshahi University of Engineering and Technology (RUET) since January 23, 2024. His research interests include medical image processing, segmentation, localization, and developing efficient deep-learning models.
Field of Research
  •  Image Classification, Segmentation, Localization
  •  Medical Image Processing
  •  Deep Learning
  •  Machine Learning
https://scholar.google.com
  •  First Joined: 23rd Jan, 2024
  •      Dept. of Electrical & Computer Engineering

Position

Education

More about Md. Faysal Ahamed
Book / Book Chapter
3
Journal Articles
9
Conference Papers
5
Standard List of Bibliography
SL Authors Title Publisher Details Publication Year Type
1 M. F. Ahamed et al., Malaria Parasite Classification from RBC Smears Using Lightweight Parallel Depthwise Separable CNN and Ridge Regression ELM by Integrating SHAP Techniques Computer and Electrical Engineering, Elsevier | IF: 4.3, Q1 | (Under Review) 2024 Journal
2 M. Nahiduzzaman, M. F. Ahamed, N. S. Alghamdi, and S. M. R. Islam SHAP-Guided Gastrointestinal Disease Classification with Lightweight Parallel Depthwise Separable CNN and Ridge Regression ELM Expert Systems with Applications, Elsevier | IF: 8.5, Q1 | (Under Review) 2024 Journal
3 M. F. Ahamed, A. Salam, M. Nahiduzzaman, M. A. Al-Wadud, S. M. R Islam Streamlining Plant Disease Diagnosis with Convolutional Neural Networks and Edge Devices Neural Computing & Application, Springer| IF: 6, Q1 | (Under Review) 2024 Journal
4 M. Naznine, M. Nahiduzzaman, M. J. Karim, M. F. Ahamed et al., PLDs-CNN-Ridge-ELM: A parallel lightweight two stage waste classification model guided by SHAP Expert Systems with Applications, Elsevier | IF: 8.5, Q1 | (Under Review) 2024 Journal
5 M. F. Ahamed et al. Automated Colorectal Polyps Detection from Endoscopic Images using MultiResUNet Framework with Attention Guided Segmentation Human-Centric Intelligent Systems (HCIN), Springer | (Under Review)) 2024 Journal
6 M. F. Ahamed et al. Optimizing Skin Lesion Segmentation with UNet and Attention-Guidance Utilizing Test Time Augmentation 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT), Dhaka, Bangladesh 2024 Conference
7 M. F. Munwar, M. A. Ahamed et al., Object Detection using Machine Learning: A Comprehensive Review of Techniques and Applications International Journal of Biomedical Imaging, hindawi | IF: 8.11, Q2 2024 Journal
8 M. F. Ahamed et al., IRv2-Net: A Deep Learning Framework for Enhanced Polyp Segmentation Performance Integrating InceptionResNetV2 and UNet Architecture with Test Time Augmentation Techniques Sensors, MDPI | IF: 3.9, Q1 | 2023 2023 Journal
9 M. F. Ahamed et al., A Review on Brain Tumor Segmentation Based on Deep Learning Methods with Federated Learning Techniques Computerized Medical Imaging and Graphics, Elsevier | IF: 5.7, Q1 2023 Journal
10 O. Sarkar, M. R. Islam, M. K. Syfullah, M. T. Islam, M. F. Ahamed, M. Ahsan, and J. Haider An Empirical Multi-Classification Approach of Classifying Lung Affected Diseases Utilizing Multi-Scale CNN Model Technologies, MDPI | IF: 3.6, Q1 2023 Journal
11 M. F. Ahamed, M. R. Islam, T. Hossain, K. Syfullah, and O. Sarkar Classification and segmentation on multi-regional brain tumors using volumetric images of MRI with customized 3D U-Net Framework Proceedings of International Conference on Information and Communication Technology for Development (ICICTD), pp. 223–234. 2023 Book Chapter
12 M. F. Ahamed, M. R. Islam, M. Nahiduzzaman, and M. E. H. Chowdhury Interpretible Deep Learning Model for Tuberculosis detection technique using X-ray images Proceedings of Surveillance, prevention, and control of infectious diseases: An AI perspective –Springer 2023 Book Chapter
13 P. Chowdhury, E. M. Eumi, O. Sarkar, M. F. Ahamed Bangla News Classification Using GloVe Vectorization, LSTM, and CNN Proceedings of the International Conference on Big Data, IoT, and Machine Learning. Lecture Notes on Data Engineering and Communications Technologies, vol 95. Springer, Singapore, 2023 2023 Book Chapter
14 T. T. Khan, A. Hassan, M. F. Ahamed, and S. Islam Multi-label Bengali Abusive Comments Classification using Problem Transformation Method 2023 20th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE). Mexico City, Mexico. 2023 Conference
15 O. Sarkar, M. F. Ahamed, T. T. Khan, M. K. Ghosh, and M. R. Islam An Experimental Framework of Bangla Text Classification for Analyzing Sentiment Applying CNN & BiLSTM 2021 2nd International Conference for Emerging Technology (INCET), Belagavi, India, 2021, pp. 1-6 2021 Conference
16 O. Sarkar, M. F. Ahamed, and P. Chowdhury Forecasting & Severity Analysis of COVID-19 Using Machine Learning Approach with Advanced Data Visualization 2020 23rd International Conference on Computer and Information Technology (ICCIT)), Dhaka, Bangladesh, 2020, pp. 1-6 2020 Conference
17 M. F. Ahamed, O. Sarkar, and A. Matin Instance Segmentation of Visible Cloud Images Based on Mask R-CNN Applying Transfer Learning Approach 2020 2nd International Conference on Advanced Information and Communication Technology (ICAICT), Dhaka, Bangladesh, 2020, pp. 257-262 2020 Conference
  •  Excellent Research Award, ECE department (2022)
  •  Student of the Year Award for excellent B. Sc. academic performance (2nd, 3rd year)
  •  Most Popular Award - IEEE YESIST12 Maker Fair Track (IEEE REGION10), Thailand
  •  2017-2022: Technical Scholarship in B.Sc. Engineering from RUET
Phd Students
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Masters Students
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Undergraduate Students
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Activity Description