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Dr. G M Atiqur Rahaman

 

Postdoctoral Researcher

Machine Perception and Interaction Lab

Center for Applied Autonomous Sensor Systems(AASS)

Örebro University, Sweden

https://mpi.aass.oru.se/

 gmatiqur@gmail.com, atiqur.rahaman@oru.se

Research Interests

 

  • artificial Intelligence
  • machine learning
  • computer vision
  • spectral image processing and analysis
  • Color science      
  • medical image analysis    

               

Education

 Ph.D. in Computer Science
 School of Computing, University of Eastern Finland
 Focus: Machine Learning based Spectral Image Analysis 
 
Licentiate of Technology (Lic.)
Faculty of Science Technology and Media,  Mid Sweden Universit
Focus: Microscopic Image Analysis for Printing Color Modeling
 
EU Joint Master Degree in Color in informatics and Media Technology (CIMET
Specialization: signal, image, and vision
The Degree consists of the following two national degrees: 
 M.Sc. in Computer Science (University of Eastern Finland + University of Jean-Monnet (France))
 M.Sc. in “Optics, Image, and Vision" (University of Granada, Spain+ University of Jean-Monnet (France))

B.Sc. Engg. in Computer Science and Engineering
Computer Science and Engineering Discipline, Khulna University
Thesis: Iso surface construction technique of volumetric data for medical imaging

 

 

Awards

 

EU Marie Curie Fellowship (Early stage researcher)
EU Erasmus Mundus Scholarship
Khulna University Merit Scholarship
Education Board Merit Scholarships for SSC and HSC

 

 

Language Skills

        Bengali   English   Spanish    French    Finnish 

 

 

Countries visited

 

         USA   UK   Ireland   Japan   France    Spain    Finland    Germany    Norway    Sweden    Portugal Netherlands  Belgium  India     

 

Publications (All are Peer Reviewed Articles)

Books

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)

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)

 
Book Chapters

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_3

Md. S. Jamil,  S. P. Banik, , G.M.A. Rahamana, S. Saha (2021). Advanced GradCAM++: Improved Visual Explanations of CNN’s decision in Diabetic Retinopathy. Proc. of International Conference on Big Data, IoT and Machine Learning (BIM 2021) (In Press, to be appear in Computer Vision and Image Analysis for Industry 4.0 by Taylor and Francis)

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

slam 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

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

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

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

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

Journals

S. Saha, G.M.A. Rahaman, 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 5.07, CS: 6.9)

 

Md.M.R. Rana, A. Hasnat, G.M.A. Rahaman (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 1.81, CS: 5)

 

G. M. A. . Rahaman, 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

 

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. (IF 3.427)       https://doi.org/10.3390/s20164379

 

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. J. Image Processing, IET (IF: 1.78, CS:4.0), https://doi.org/10.1049/ipr2.12018

 

Saha S., Rahaman G.M.A., Islam S.T., Frost S., Kanagasingam Y. (2019) Retinal image registration relying on robust binary description of bifurcation point. J. Medical Systems, Springer (IF: 2.415, Under Review)

 

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

 

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. (IF: 1.428)

 

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 (Citations# 32 as of Sep 2022)

 

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 (Citations# 14 as of Sep 2022) DOI: 10.4304/jcp.5.12.1800-1809

G.M.A. Rahaman, 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 (Citations# 93 as of Sep 2022)

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)

Conference (Peer Reviewed) Papers

G.M.A. Rahaman, M. Längkvist, A. Loufti (2022, Sep), Deep Learning based Aerial Image Segmentation for Computing Green Area Factor, Proc. of the 10th European Workshop on Visual Information Processing, Lisbon, Portugal (In press, to be appear in IEEE Xplore)

 

P. Protik, G.M.A. Rahaman, S.Saha(2021). Automated Detection of Diabetic Foot Ulcer using Convolutional Neural Network , Proc. of International Conference on 4th Industrial Revolution and Beyond (IC4IR) 2021 (In press, to be appear in IEEE Xplore)

 

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.

 

Kazi Mahmud Hasan, Abdullah-Al- Nahid, Md. Abdul Alim, Md. Maniruzzaman, G M Atiqur Rahaman, S.H. Shah Newaz, Md. Shamim Ahsan (2020, June). Design and Development of an Aircraft Type   Multi-functional Autonomous Drone. (Accepted) Proc. of IEEE Conf. on Technology for Impactful Sustainable Development (TENSYMP2020), Dhaka, 5-7 June , 2020.

 

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

 

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

 

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

 

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

 

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

 

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

 

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 

 

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

 

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.

 

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.

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