Projects

Machine Learning

Siemon, M.S.N., Shihavuddin, A.S.M. & Ravn-Haren, G. Sequential transfer learning based on hierarchical clustering for improved performance in deep learning-based food segmentation. Sci Rep 11, 813 (2021). https://doi.org/10.1038/s41598-020-79677-1

https://www.nature.com/articles/s41598-020-79677-1?fbclid=IwAR24j1ExfbP2bFGH6w4bVifa1BQ7VC0aLE4E6rgB6wAjO3b3Afw556xV5iA

Chen, X.; Eder, M.A.; Shihavuddin, A.; Zheng, D. A Human-Cyber-Physical System toward Intelligent Wind Turbine Operation and Maintenance. Sustainability 2021, 13, 561.

https://www.mdpi.com/2071-1050/13/2/561

Haque, W.A., Arefin, S., Shihavuddin, A.S.M. and Hasan, M.A., 2020. DeepThin: A novel lightweight CNN architecture for traffic sign recognition without GPU requirements. Expert Systems with Applications, p.114481.

https://www.sciencedirect.com/science/article/abs/pii/S0957417420311283

Chen, X., Shihavuddin, A.S.M., Madsen, S.H., Thomsen, K., Rasmussen, S. and Branner, K., 2020. AQUADA: Automated quantification of damages in composite wind turbine blades for LCOE reduction. Wind Energy.

https://onlinelibrary.wiley.com/doi/full/10.1002/we.2587?af=R

Renewable Energy

Md Hasan Maruf, Mohammad Asif ul Haq, Suman Kumar Dey, Ahmed Al Mansur, A.S.M. Shihavuddin, Adaptation for sustainable implementation of Smart Grid in developing countries like Bangladesh, Energy Reports, Volume 6, 2020, Pages 2520-2530, ISSN 2352-4847.

(https://www.sciencedirect.com/science/article/pii/S2352484720313214 )

Tausen Marni, Clausen Marc, Moeskjær Sara, Shihavuddin ASM, Dahl Anders Bjorholm, Janss Luc, Andersen Stig Uggerhøj, Greenotyper: Image-Based Plant Phenotyping Using Distributed Computing and Deep Learning, Frontiers in Plant Science, VOLUME=11, YEAR=2020, PAGES=1181, 10.3389/fpls.2020.01181

(https://www.frontiersin.org/articles/10.3389/fpls.2020.01181/full?report=reader )

Haq, M.A.; Islam, A.; Shihavuddin, A.; Maruf, M.H.; Al Mansur, A.; Hassan, M.Y. Enhanced Energy Savings in Indoor Environments with Effective Daylight Utilization and Area Segregation. Symmetry 2020, 12, 1313.

(https://www.mdpi.com/2073-8994/12/8/1313)

Deep Learning related works

Publication:

1. Gómez-Ríos, A., Tabik, S., Luengo, J., Shihavuddin, A.S.M. and Herrera, F., 2019. Coral species identification with texture or structure images using a two-level classifier based on Convolutional Neural Networks. Knowledge-Based Systems, p.104891.

(https://www.sciencedirect.com/science/article/abs/pii/S0950705119303569 )

2. Gómez-Ríos, A., Tabik, S., Luengo, J., Shihavuddin, A.S.M., Krawczyk, B. and Herrera, F., 2018. Towards Highly Accurate Coral Texture Images Classification Using Deep Convolutional Neural Networks and Data Augmentation. arXiv preprint arXiv:1804.00516.

(https://arxiv.org/abs/1804.00516)

3. Gómez-Rıos, A., Tabik, S., Luengo, J., Herrera, F., Shihavuddin, A.S.M. and Krawczyk, B., 2019. Redes Neuronales Convolucionales para Una Clasificacion Precisa de Imagenes de Corales. In XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (pp. 1171-1176).

(http://hallsi.ugr.es/temp/CAEPIA2018/web/docs/CAEPIA2018_paper_212.pdf)

Automated wind turbine damage detection

4. ASM Shihavuddin, Xiao Chen, Vladimir Fedorov, Nicolai Andre Brogaard Riis, Anders Nymark Christensen, Kim Branner, Anders Bjorholm Dahl, Rasmus Reinhold Paulsen, Wind turbine maintenance cost reduction by deep learning aided drone inspection analysis, Energies, Maintenance Management of Wind Turbines, 12 (4)

(https://www.mdpi.com/1996-1073/12/4/676)

Others

5. Othmani, A.A., Basu, S., Shrivastava, A.N., Aslan, S., De Carli, F., Afua, A.D., Shihavuddin, A.S.M. and Nait-Ali, A., 2019. Biometrics from Cellular Imaging. In Biometrics under Biomedical Considerations (pp. 229-252). Springer, Singapore.

(https://link.springer.com/chapter/10.1007/978-981-13-1144-4_11)

Nuclei Segmentation

1. 34th position in the Kaggle nuclei segmentation challenge (superbowl)

Microscopic image analysis toolbox development

Publication:

1. Al Jord, A., Shihavuddin, A., d’Aout, R.S., Faucourt, M., Genovesio, A., Karaiskou, A., Sobczak-Thépot, J., Spassky, N. and Meunier, A., 2017. Calibrated mitotic oscillator drives motile ciliogenesis. Science, 358(6364), pp.803-806.

(http://science.sciencemag.org/content/358/6364/803)

2. Ortiz-Álvarez, G., Daclin, M., Shihavuddin, A., Lansade, P., Fortoul, A., Faucourt, M., Clavreul, S., Lalioti, M.E., Taraviras, S., Hippenmeyer, S. and Livet, J., 2019. Adult Neural Stem Cells and Multiciliated Ependymal Cells Share a Common Lineage Regulated by the Geminin Family Members. Neuron.

(https://www.sciencedirect.com/science/article/pii/S0896627319300789)

Code: https://github.com/biocompibens/CAMC

3. Foerster, P., Daclin, M., Asm, S., Faucourt, M., Boletta, A., Genovesio, A. and Spassky, N., 2017. mTORC1 signaling and primary cilia are required for brain ventricle morphogenesis. Development, 144(2), pp.201-210.

(http://dev.biologists.org/content/144/2/201)

4. Mahuzier, A., Shihavuddin, A., Fournier, C., Lansade, P., Faucourt, M., Menezes, N., Meunier, A., Garfa-Traoré, M., Carlier, M.F., Voituriez, R. and Genovesio, A., 2018. Ependymal cilia beating induces an actin network to protect centrioles against shear stress. Nature communications, 9(1), p.2279.

(https://www.nature.com/articles/s41467-018-04676-w)

SME Projection < FastSME

Publication:

1. Shihavuddin, Asm, Sreetama Basu, Elton Rexhepaj, Felipe Delestro, Nikita Menezes, Séverine M. Sigoillot, Elaine Del Nery, Fekrije Selimi, Nathalie Spassky, and Auguste Genovesio, Smooth 2D manifold extraction from 3D image stack.Nature Communications 8 (2017): 15554.

2. Basu, S., Rexhepaj, E., Spassky, N., Genovesio, A.,Reinhold, R. and Shihavuddin, A., 2018. FastSME: faster and smoother manifold extraction from 3D stack. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (pp. 2281-2289).

(https://www.nature.com/articles/ncomms15554)

Code: https://github.com/biocompibens/SME

FIJI: https://imagej.net/SME_Projection

DATA: https://dataverse.harvard.edu

Reef Classification

Publication:

1. Computer Vision inVehicle Technology: Land, Sea and Air , Nuno Gracias, Rafael Garcia, RicardCampos, Natalia Hurtos, Ricard Prados, ASMShihavuddin, Tudor Nicosevici, Armagan Elibol, Laszlo Neumann, JavierEscartin, (Ed. A.M. Lopez, A. Imiya, T. Pajdla, J.M. Alvarez), Wiley, ISBN: 978-1-118-86807-2, pp.127-157, 2017.

(http://onlinelibrary.wiley.com/doi/10.1002/9781118868065.ch7/summary)

2. Geostatistics for Context-Aware Image Classification, F Codevilla, SSC Botelho, N Duarte, S Purkis, ASM Shihavuddin, Computer Vision Systems, ICVS 228-239, 2015

(https://link.springer.com/chapter/10.1007/978-3-319-20904-3_22)

3. Improved Supervised Classification of Underwater Military Munitions Using Height Features Derived from Optical Imagery, ACR Gleason, ASM Shihavuddin, N Gracias, G Schultz, BE Gintert, OCEANS 2015-MTS/IEEE Washington, 2015

(https://www.researchgate.net/publication/311887572_Improved_Supervised_Classification_of_Underwater_Military_Munitions_Using_Height_Features_Derived_from_Optical_Imagery)

4. Automated Detection of Underwater Military Munitions Using Fusion of 2D and 2.5 D Features From Optical Imagery, ASM Shihavuddin, N Gracias, R Garcia, R Campos, ACR Gleason, 0Marine Technology Society Journal (MTS) 48 (4), 61-71, 3, 2014

(https://www.researchgate.net/publication/265340758_Automated_Detection_of_Underwater_Military_Munitions_Using_Fusion_of_2D_and_25D_Features_From_Optical_Imagery)

5. Automated classification and thematic mapping of bacterial mats in the North Sea, ASM Shihavuddin, N Gracias, R Garcia, J Escartin, R Birger Pedersen, OCEANS-Bergen, 2013 MTS/IEEE, 1-8, 3, 2013

(http://ieeexplore.ieee.org/abstract/document/6608111/)

6. Image-based coral reef classification and thematic mapping, ASM Shihavuddin, N Gracias, R Garcia, ACR Gleason, B Gintert, Remote Sensing 5 (4), 1809-1841, 16, 2013

(http://www.mdpi.com/2072-4292/5/4/1809)

7. Optical methods to monitor temporal changes at the seafloor: The Lucky Strike deep-sea hydrothermal vent field (Mid-Atlantic Ridge), J Escartin, R Garcia, T Barreyre, M Cannat, N Gracias, ASM Shihavuddin, Underwater Technology Symposium (UT), 2013 IEEE International, 1-6, 2, 2013

(http://ieeexplore.ieee.org/abstract/document/6519838/)

Code: http://www.mdpi.com/2072-4292/5/4/1809

Dataset: https://data.mendeley.com/datasets/86y667257h/2

Original image vs Processed image

Online sunflicker removal

Publication:

1. Image-based coral reef classification and thematic mapping, ASM Shihavuddin, N Gracias, R Garcia, ACR Gleason, B Gintert, Remote Sensing 5 (4), 1809-1841, 16, 2013(http://www.mdpi.com/2072-4292/5/4/1809)

2. Online Sunflicker Removal using Dynamic Texture Prediction, ASM Shihavuddin, N Gracias, R Garcia, International Conference on Computer Vision Theory and Applications (VISAPP), 2012(https://www.researchgate.net/profile/Rafael_Garcia23/publication/267242834_Online_sunflicker_removal_using_dynamic_texture_prediction/links/545815b30cf2bccc49111d2b/Online-sunflicker-removal-using-dynamic-texture-prediction.pdf

With sunflicker effect vs without sunflicker effect

Others

Weed classification

Ahmed, F., Bari, A.H., Shihavuddin, A.S.M., Al-Mamun, H.A. and Kwan, P., 2011, November. A study on local binary pattern for automated weed classification using template matching and support vector machine. In Computational Intelligence and Informatics (CINTI), 2011 IEEE 12th International Symposium on (pp. 329-334). IEEE.

Facial expression recognition

Ahmed, F., Hossain, E., Bari, A.H. and Shihavuddin, A.S.M., 2011, November. Compound local binary pattern (CLBP) for robust facial expression recognition. In Computational Intelligence and Informatics (CINTI), 2011 IEEE 12th International Symposium on (pp. 391-395). IEEE.

Stock price prediction based on news attributes

Shihavuddin, A.S.M., Ambia, M.N., Arefin, M.M.N., Hossain, M. and Anwar, A., 2010, August. Prediction of stock price analyzing the online financial news using Naive Bayes classifier and local economic trends. In Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on (Vol. 4, pp. V4-22). IEEE.

Pipe inspection using omnidirectional camera

Islam, M.R., Naser, M.A., Hasan, M.R., Shihavuddin, A.S.M. and Hoque, M.A., 2011, December. Using catadioptric sensor to obtain image of the inner surface of a pipe and detection and analysis of faults by image processing. In Computer and Information Technology (ICCIT), 2011 14th International Conference on (pp. 607-610). IEEE.

Robot path estimation

Ahmed, K., Munir, M.S., Shihavuddin, A.S. M., Hoque, M.A. and Islam, K.K., 2008, December. Towards Autonomous Robot Operation: Path Map Generation of an Unknown Area by a New Trapezoidal Approximation Method Using a Self Guided Vehicle and Shortest Path Calculation by a Proposed SRS Algorithm. In Pacific Rim International Conference on Artificial Intelligence (pp. 593-602). Springer, Berlin, Heidelberg.

Shihavuddin, A.S.M., Fadlullah, N.M. and Islam, K.K., 2007. Micro-controller operated robot using photo sensor guiding system. In 1st international conference on control, instrumentation and mechatronics, CIM.

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