Dr. G M Atiqur Rahaman
Professor
Address:
Computer Science and Engineering Discipline, Khulna University, Khulna-9208, Bangladesh.
I am a computer scientist and engineer, currently employed as a Professor in Computer Science and Engineering Discipline of the renowned Khulna University of Bangladesh. I have institutional training and expertise in Spectral Imaging and machine-learning-based image analysis. I was a postdoctoral fellow in the Machine Perception and Interaction (MPI) lab, in the Center for Applied Autonomous Sensor Systems (AASS) of Örebro University, Sweden. I have worked with Örebro University Hospital, Örebro Municipality, and the Swedish Institute for Forest Research. I have designed and implemented various deep-learning methods for solving challenging industrial problems. The contributions have been published in a high-quality journal and European conference.
I achieved Ph.D. degree in Computer Science from the School of Computing at the highly-ranked University of Eastern Finland (UEF) attached to the Computational Spectral Imaging Research Group. The research focus was on developing a machine learning approach to analyze multispectral images. I have also completed a Licentiate of Technology degree in Engineering Physics from Mid Sweden University with an EU Marie Curie Fellowship under the project CP7.0 led by NTNU. During this study, I developed innovative methods to analyze halftone microscale images and proposed an extension of a classical color reproduction model useful for the Printing and Graphics Arts Industry. The application area was in the cultural heritage and spectral printing industry.
I completed the EU Erasmus Mundus double Master degree (CIMET) jointly awarded ( due to extraordinary results) by the University of Granada Spain, University Jean-Monnet France, Norwegian University of Science and Technology (NTNU), and UEF. The main fields of study were Spectral Imaging, Signal, and Vision. In my M.Sc. thesis, I proposed novel techniques to analyze multispectral retinal images to detect and classify various diabetic retinopathies. During 04 years of study of B.Sc. Engineering in Computer Science and Engineering discipline, I worked for one year on a bachelor thesis in MRI medical image analysis. An algorithm was proposed to render voxel-based surface to reconstruct the scanned brain image.
My overall
research area and interests are in developing machine/deep learning-based
computational techniques for various applications in the intersection fields of
spectral imaging, color science, computer vision, pattern recognition and
modeling. My current research focuses on developing Machine
Learning/Neural Network/Deep Learning based methods for image analysis in
different medical applications. Throughout my academic and research career, I have
worked with high-quality international researchers both in academia and
industries around the world. Over the last 20 years, not only I have been
involved in pursuing post-graduate studies in Europe but also involved in
teaching, researching and supervising students of Computer Science at the university
level. So far I have supervised as the main supervisor or evaluated as an
expert member a number of thesis and projects in computer science at
undergraduate and graduate levels. Currently, I am supervising Ph.D., M.Sc. and
B.Sc. thesis students working on machine learning/deep learning-based method
development to analyze images in different
applications.
I have
scientific publications and documented knowledge in the fields computer vision,
deep learning, multispectral imaging and image analysis. I have notable
experience in teaching at the university level. Solid and relevant
multi-disciplinary education, training, skills, and work experiences in
high-quality international research and academic environments have made me a
strong candidate for an academic administration or research position.
I am proficient
in both independent work and collaborative teamwork, with a commitment to
excellence, strong ethics, and respect for diverse viewpoints. I am eager to
contribute innovative ideas, solve real-world problems, and disseminate
knowledge within the academic community. My multidisciplinary education,
diverse skills, and extensive teaching and research experience equip me to
develop a high-quality international academic and research environment.
My diverse educational background, extensive research skills, and
substantial teaching experience equip me for leadership in the academic arena.
I am committed to creating a high-quality academic and research environment and
aspire to contribute to building a knowledge-based society in Bangladesh,
enhancing the quality of life through education and innovation.
Postdoctoral Fellow, Machine Perception and Interaction Lab, Orebro University, Sweden 2021-2023Research Area: Artificial Intelligence, Machine Learning, Deep learning |
Ph.D. in Computer Science, University of Eastern Finland, Finland 2017 Dissertation: Use of Reflectance Measurements to Study Turbid Media by Imaging |
Licentiate of Technology in Engineering Physics, Mid Sweden University, Sweden 2014 Dissertation: Image Analysis Approach for modelling Color in Printing |
M.Sc. in Computer Science (Univ. of Eastern Finland + Univ. Jean-Monnet, France) 2011 M.Sc. in Optics, Image and Vision, (Univ. of Granada, Spain + Univ. Jean-Monnet France) 2010 Thesis: Retinal Spectral Image Analysis for Diabetic Retinopathy Obtained Grade: B (80%-89%) marks |
B.Sc. Engg. in Computer Science and Engg., Khulna University, Bangladesh 2003 Thesis: Iso-surface Construction Technique of Volumetric Data for Medical Imaging Obtained CGPA: 3.81/4.0 (Distinction, 2nd position in merit list) |
Higher Secondary Certificate (HSC) Exam., Notre Dame College, Dhaka, Bangladesh 1998 Obtained marks: 89.4% |
Secondary School Certificate (SSC) Exam., Khulna Zilla School, Khulna, Bangladesh 1996 Obtained marks: 85.3% |
Artificial Intelligence
Deep Learning
Machine Learning
Computer Vision
Color Science
Spectral/Colour Imaging
Current Research Project/Collaboration
SL | Title | Research Role | Awarded Date | Completion Date | Funding Agency |
---|---|---|---|---|---|
No Research Project Available |
Position | Name of the Institution | Duration |
Postdoctoral Fellow | Machine Perception and
Interaction (MPI) lab, Centre for Applied Autonomous Sensor Systems
(AASS), Örebro University, Sweden | 2021- 2023 |
Professor | Computer Science and Engineering (CSE) Discipline, Khulna University, Bangladesh | 2017- to date |
Associate Professor | CSE Discipline, Khulna University, Bangladesh | 2011- 2017 |
Assistant Professor | CSE Discipline, Khulna University, Bangladesh | 2007- 2011 |
Lecturer | CSE Discipline, Khulna University, Bangladesh | 2006-2007 |
Lecturer | CSE Faculty, Patuakhali Science and Technology University, Bangladesh | 2004- 2006 |
Part-time teacher | Khulna Agricultural University, Dhaka International University, Northern University of Business and Technology, Asian University, ICMAB, College Teachers Training Institute, etc. | --------------- |
EU Marie Curie Fellowship for PhD (2012-2015)
EU Erasmus Mundus Scholarship for double M.Sc. degree (2009-2011)
Bangladesh ICT Division Fellowship (2016)
Khulna University Merit Scholarship
H.S.C. and S.S.C. Education Board Merit Scholarships
Supervision
SL | Title | Degree | Role | Start Date | End Date |
---|---|---|---|---|---|
No Supervision Available |
No Data Available
coming soon...
Publications (All are Peer Reviewed Articles)
Journals/Book Chapters
1.
G. M. Atiqur Rahaman, M.
Längkvist and A. Loutfi (2024). Deep Learning
Based Automated Estimation of Urban Green Space Index from Satellite Image: A
Case Study, Urban Forestry & Urban Greening,
Volume 97,128373, doi: 10.1016/j.ufug.2024.128373. (IF 6.0)
2.
Azoad ahnaf SM, Saha S, Frost S,
Rahaman G.M.A. Understanding and interpreting CNN’s decision
in optical coherence tomography-based AMD detection. European Journal of Ophthalmology. 2023;0(0).
doi:10.1177/11206721231199126 (IF 1.6)
3.
S. Saha, Rahaman G.M.A., T. Islam, M. Akter, S. Frost, Y.
Kanagasingam(2021), Retinal image
registration using log-polar transform and robust description of bifurcation
points,
Biomedical Signal Processing and Control,
Volume 66, 102424, ISSN 1746-8094, https://doi.org/10.1016/j.bspc.2021.102424.
(IF 4.9)
4.
Md.M.R. Rana, A. Hasnat, Rahaman G.M.A., (2022), SMIFD-1000: Social media image forgery detection database, Forensic Science International: Digital
Investigation, Volume 41, 301392, ISSN 2666-2817, https://doi.org/10.1016/j.fsidi.2022.301392. (IF 2.0)
5.
Rahaman G.M.A., S. R. . Ali, and S. . Paul (2021), Diabetic
Retinopathy Lesion Detection From Multispectral Retinal Images Through Neural
Network, Khulna Univ. Stud., pp. 41–55, Sep., https://doi.org/10.53808/KUS.2020.17.1and2.2001-E
6.
Rahaman G.M.A., Jussi Parkkinen, and Markku Hauta-Kasari(2020). A Novel Approach to Using Spectral Imaging to
Classify Dyes in Colored Fibers. Sensors 20, no. 16:
4379.
https://doi.org/10.3390/s20164379 (IF 3.4)
7.
Sayed M.A., Saha S., Rahaman G.M.A., Ghosh T.K.,
Kanagasingam Y (2020) An Innovate
Approach for Retinal Blood Vessel Segmentation using Mixture of Supervised and
Unsupervised Methods. Image Processing, IET, (https://doi.org/10.1049/ipr2.12018 (IF 1.78)
8.
Rahaman
G.M.A, Rajon A H M, Rahman A. (2012), Effective Approach for
Automatic Detection of Vessels, Optic Disk and Macula: Retinal Spectral Image
Analysis Perspective. International journal of Applied Research in
Computer Science and Information Technology (IJAR-CSIT), Vol. 2
9.
Rahaman
G.M.A., Hossain M. M., Arif M. A., Chowdhury E. & Debnath S. (2010). Mining structured objects (data records) based on maximum region
detection by text content comparison from website. International
Journal of Electrical and Computer Sciences (IJECS-IJENS),
10(2), 22-28.
10.
Chatterjee
A., Shuvankar M., Rahaman G.M.A., and Abu S.M.A. (2010), Fingerprint identification and verification system by minutiae
extraction using artificial neural network. The International
Journal of Computer and Information Technology JCIT 1(1) pp. 12-16
11. Ripon K.S.N., Rahman A. and Rahaman G.M.A. (2010) A domain-independent data cleaning algorithm for detecting similar-duplicates. Journal of Computers
5(12) pp. 1800-1809 DOI: 10.4304/jcp.5.12.1800-1809
12.
Rahaman G.M.A., Md. M. Hossain (2009). Automatic Defect
Detection and Classification Technique from Image: A Special Case Using Ceramic
Tiles. arXiv:0906.3770
[cs.CV], https://doi.org/10.48550/arXiv.0906.3770
13. Rahaman G.M.A. and Alam A.F.M.(2008). An Efficient Approach for fast Fingerprint Identification based
on Minutiae Local Structure. Southeast University Journal of Engineering
and Technology SEUJSE 2(2) (print version only)
14.
Protik, P.,
Rahaman, G. M.A., & Saha, S. (2023). Automated Detection of Diabetic Foot Ulcer Using Convolutional
Neural Network. In The Fourth Industrial Revolution and Beyond:
Select Proceedings of IC4IR+ (pp. 565-576). Singapore: Springer Nature
Singapore. DOI: https://doi.org/10.1007/978-981-19-8032-9_40
15.
Jamil, M. S., Banik, S. P., Rahaman, G.M.A.,
& Saha, S. (2023). Advanced
GradCAM++:
Improved
Visual Explanations of CNN’s decision in Diabetic Retinopathy.
In Computer Vision and Image Analysis for Industry 4.0 (pp. 64-75). 6000 Broken
Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press.
16.
S. Pal, and G.M.A. Rahaman (2022). Image Forgery Detection Using CNN and Local
Binary Pattern-Based Patch Descriptor. In Innovations in
Computational Intelligence and Computer Vision, pp. 429-439. Springer,
Singapore. https://doi.org/10.1007/978-981-19-0475-2_38 (Best paper in Deep Learning track)
17.
Sayed
M.A., Saha S., Rahaman G.M.A., Ghosh T.K., Kanagasingam Y. (2019) A Semi-supervised Approach to Segment Retinal Blood Vessels in
Color Fundus Photographs. In:
Artificial Intelligence in Medicine, AIME 2019. Lecture Notes in Computer
Science, vol 11526, pp 347-351,
Springer, Cham. DOI: 10.1007/978-3-030-21642-9_44
18. Islam S.T., Saha S., Rahaman G.M.A., Dutta D., Kanagasingam
Y. (2019) An Efficient Binary Descriptor to Describe Retinal
Bifurcation Point for Image Registration. In: Pattern Recognition and Image Analysis, IbPRIA 2019.
Lecture Notes in Computer Science, vol 11867. Springer, Cham. DOI: 10.1007/978-3-030-31332-6_47
19.
Ghosh
T.K., Saha S., Rahaman G.M.A., Sayed M.A., Kanagasingam Y. (2019) Retinal Blood Vessel Segmentation: A Semi-supervised Approach.
In: Pattern Recognition and Image Analysis, IbPRIA 2019. Lecture Notes in Computer Science, vol 11868.
Springer, Cham. DOI: 10.1007/978-3-030-31321-0_9
20.
Rahaman
G.M.A., Hasnat M.A., Mourya R. (2015) Collection, Analysis and
Representation of Memory Color Information. In: Computational Color Imaging. CCIW 2015. Lecture Notes
in Computer Science, vol 9016, pp.
93–103, Springer, Switzerland. DOI: 10.1007/978-3-319-15979-9_9
21.
Rahaman
G.M.A., Norberg O., Edström P. (2015) Experimental Analysis for
Modeling Color of Halftone Images.
In: Computational Color Imaging. CCIW 2015. Lecture Notes in Computer Science,
vol 9016,
pp. 69–80, Springer, Switzerland. DOI: 10.1007/978-3-319-15979-9_7
22. Rahaman G.M.A., Parkkinen J., Hauta-Kasari M., Norberg O.
(2013) Retinal Spectral Image Analysis Methods Using
Spectral Reflectance Pattern Recognition. In: Computational Color Imaging. CCIW 2013. Lecture Notes
in Computer Science, vol 7786, pp. 224–238, Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-36700-7_18
23. G. M. A. Rahaman, M. Längkvist and A. Loutfi, Deep Learning based Aerial Image Segmentation for
Computing Green Area Factor, 2022 10th European Workshop on Visual
Information Processing (EUVIP), Lisbon, Portugal 2022, pp. 1-6, doi: 10.1109/EUVIP53989.2022.9922743
24.
Protik, P., Rahaman, G.M.A, Saha, S.
(2023). Automated
Detection of Diabetic Foot Ulcer Using Convolutional Neural Network. In: Hossain, M.S., Majumder,
S.P., Siddique, N., Hossain, M.S. (eds) The Fourth Industrial Revolution and
Beyond. Lecture Notes in Electrical Engineering, vol 980. Springer, Singapore. doi:
10.1007/978-981-19-8032-9_40
25.
S. M. A.
Ahnaf, G. M. A. Rahaman and S. Saha, (2021), Understanding CNN's
Decision Making on OCT-based AMD Detection", 2021 International Conference on Electronics,
Communications and Information Technology (ICECIT), pp. 1-4, doi: 10.1109/ICECIT54077.2021.9641246.
26.
K. M. Hasan et al., Design and Development of
an Aircraft Type Multi-functional Autonomous Drone, 2020 IEEE Region 10 Symposium (TENSYMP),
2020, pp. 734-737, doi: 10.1109/TENSYMP50017.2020.9230929
27. Md. Mehedi Rahman, , Jannatul Tajrin, Abul Hasnat,
Naushad UzZaman, and G. M. Atiqur Rahaman (2019, December). SMIFD: Novel Social Media Image Forgery Detection Database. Proc. of IEEE 22nd International Conference on
Computer and Information Technology (ICCIT), 18-20 December, 2019. doi: 10.1109/iccit48885.2019.9038557
28.
Rahaman G.M.A., Parkkinen J., Hauta-Kasari M., &
Amirshahi S. H. (2017, February). Enhanced color visualization by spectral
imaging: an application in cultural heritage. In 2017 IEEE International Conference on Imaging, Vision
& Pattern Recognition (icIVPR) (pp. 1-6). IEEE. doi: 10.1109/ICIVPR.2017.7890870
29.
Rahaman G.M.A., Parkkinen J., Hauta-Kasari M., & Amirshahi S. H. (2017, February). Fiber dye classification by spectral imaging. In 2017 IEEE International Conference on
Imaging, Vision & Pattern Recognition
(icIVPR) (pp. 1-6). IEEE. DOI: 10.1109/icivpr.2017.7890872
30. Khan M. R., Rahman A. M., Rahaman G. M.
A., & Hasnat M. A. (2016, May). Unsupervised RGB-D image segmentation by
multi-layer clustering. In
2016 IEEE 5th International Conference on Informatics, Electronics and Vision
(ICIEV) (pp. 719-724). IEEE DOI: 10.1109/iciev.2016.7760095
31. Rahaman G.M.A., Norberg O., &
Edström P. (2014, February). Extension of Murray-Davies tone reproduction
model by adding edge effect of halftone dots. In: Proc. SPIE 9018, Measuring, Modeling, and Reproducing
Material Appearance, 90180F; International Society for Optics and Photonics. doi:: 10.1117/12.2037754
32.
Rahaman G.M.A., Norberg O., & Edström P. (2014,
February). Microscale halftone color image analysis:
perspective of spectral color prediction modeling. In Proc. SPIE Color Imaging XIX: Displaying, Processing,
Hardcopy, and Applications (Vol. 9015, p. 901506). International Society for
Optics and Photonics. doi: 10.1117/12.2037256
33. Rahaman G. M.A., Norberg O., &
Edström P. (2013, July). The Effect of Media Interactions in Predicting
Spectral Reflectance by Color Prediction Models. In: Proc. of 12th Congress of the International Colour
Association Newcastle upon Tyne, UK,
Vol.2, pp.593-596
34.
Arif
A.S.M., Rahaman G.M.A., Biswas G. K., & Islam, S. N. (2008, December). An efficient system for recognition of human face in different
expressions by some measured features of the face using laplacian operator. In IEEE Proc. 11th International Conference on Information
and Communication Technology (ICCIT’08),
pp. 405-410. DOI: 10.1109/iccitechn.2008.4802977
35. Alam A.F.M. , Ali I.A., Debnath R., Rahaman, G.M.A. (2008) Efficient
Fingerprint Identification and Verification System Using Minutiae Matching
Technique. In Proc. of the International
Conference on Electronics, Computer and Communication (ICECC’08), pp.: 364-367.
36. Mondal M., Rahaman G.M.A., Tarafder D.(2008). Real Time Face Recognition Using Minimum Measurements when at Least Two Thirds of the Face is Present in the Image. In: Proc. 9th International Conference on Computer and Information Technology (ICCIT 06), pp: 247-252
Books
37. Títle: Use of Reflectance Measurements to study Turbid
Media by Imaging, City:
Joensuu, Finland, Editorial: Prof. Lindsay W. Macdonald and
Docent Reiner Lenz., Year: 2017, Number of pages: 151,
ISBN: 978-952-61-2455-1, Authors: Rahaman, G M Atiqur (PhD
Thesis)
38. Títle: Image Analysis Approach for Modeling Color
Predictions in Printing , City: Sundsvall,
Sweden, Editorial: Prof. Per Edstrom, Dr. Ole Norberg and Dr. Magnus
Neuman, Year: 2014, Number of pages: 51, ISBN:
978-91-87557-32-3, Authors: Rahaman, G M Atiqur (Licentiate Thesis)