Sheng Kuang, Sheng Kuang, Henry C. Woodruff, Renee Granzier c, Thiemo J.A. van Nijnatten, Marc B.I. Lobbes, Marjolein L. Smidt, Philippe Lambin, S. Mehrkanoon, “MSCDA: Multi-level semantic-guided contrast improves unsupervised domain adaptation for breast MRI segmentation in small datasets”, Neural Networks, vol. 165, pp. 119-134, 2023 [pdf]
Onur Bilgin, Thomas Vergutz, S. Mehrkanoon, “GCN-FFNN: A two-stream deep model for learning solution to partial differential equations”, Neurocomputing, vol. 511, pp. 131-141, 2022 [pdf]
K van der Heijden, S. Mehrkanoon, “Goal-driven, neurobiological-inspired convolutional neural network models of human spatial hearing ”, Neurocomputing, vol. 470, pp. 432-442, 2022 [pdf]
D. Vanpoucke, M. Delgove, J. Stouten, J. Noordijk, N. De Vos, K. Matthysen, G. Deroover, S. Mehrkanoon, K. Bernaerts , “A machine learning approach for the design of hyperbranched polymeric dispersing agents based on aliphatic polyesters for radiation‐curable inks ”, Polymer International , vol. 470, pp. 432-442, 2022[pdf]
K. Trebing, T. Staǹczyk, S. Mehrkanoon , “Smaat-unet: Precipitation nowcasting using a small attention-unet architecture ”, Pattern Recognition Letters, vol. 145, pp. 178-186, 2021. [GitHub]
JG Fernández, S. Mehrkanoon , “Broad-UNet: Multi-scale feature learning for nowcasting tasks ”, Neural Networks 144, 419-427, 2021 [GitHub]
D. Vanpoucke, O. Knippenberg, K. Hermans, K. Bernaerts, S Mehrkanoon , “ Small data materials design with machine learning: When the average model knows best ”, Journal of Applied Physics , 128, 054901-12 , 2020 [pdf]
S. Mehrkanoon, “Deep shared representation learning for weather elements forecasting ”, Knowledge-Based Systems, Vol 179, pp. 120-128,Sept 2019[pdf][dataset]
S. Mehrkanoon, “ cross-domain neural kernel networks ”, Pattern recognition letter, Vol 125, pp. 474-480, July 2019 [pdf].
S. Mehrkanoon, “ Deep neural kernel blocks ”, Neural Networks, Vol 116, pp. 46-55, August 2019 [pdf].
S. Mehrkanoon, J.A.K. Suykens, “Deep hybrid neural-kernel networks using random Fourier features”, Neurocomputing, Vol.298, pp.46-54, July 2018 [PDF].
S. Mehrkanoon, X. Huang, J.A.K. Suykens, “Indefinite Kernel Spectral Learning”, Pattern Recognition, Vol 78, June 2018, Pages 144-153 [PDF].
S. Mehrkanoon, J.A.K. Suykens, “Regularized Semi-Paired Kernel CCA for Domain Adaptation”, IEEE Trans. Neural Netw. Learning Syst, Vol 29, pp.3199-3213, 2018. [PDF]
Y. Feng, Y. Yang, X. Huang, S. Mehrkanoon, J.A.K. Suykens, “Robust Support Vector Machines for Classification with Nonconvex and Smooth Losses,” Neural-Computation, Vol. 28, no. 6, pp. 1217-1247, 2016. [PDF]
S. Mehrkanoon, Yuri A.W. Shardt, J. A. K. Suykens, Steven X. Ding, “Estimating the Unknown Time Delay in Chemical Processes,” Engineering Applications of Artificial Intelligence, Vol. 55, pp. 2190, 2016. [PDF]
S. Mehrkanoon, O. M. Agudelo, J. A. K. Suykens, “Incremental multi-class semi-supervised clustering regularized by Kalman filtering,” Neural Networks, Vol 71, pp. 88-104, 2015. [PDF]
S. Mehrkanoon, J. A. K. Suykens, “Learning solutions to partial differential equations using LS-SVM,” Neurocomputing, Vol. 159, pp. 105-116, 2015. [PDF]
R. Mall, S. Mehrkanoon, J. A. K. Suykens, “Identifying intervals for hierarchical clustering using the Gershgorin circle theorem,” Pattern Recognition Letters, Vol 55, pp. 1-7,2015. [PDF]
S. Mehrkanoon, C. Alzate, R. Mall, R. Langone, J. A. K. Suykens, “Multiclass semi-supervised learning based upon kernel spectral clustering,” IEEE Trans. Neural Netw. Learning Syst, Vol. 26, pp. 720-733, 2015. [PDF]
S. Mehrkanoon, X. Huang, J. A. K. Suykens, “Non-parallel support vector classifiers with different loss functions,” Neurocomputing, 143(2), pp. 294-301, 2014. [PDF]
S. Mehrkanoon, S. Mehrkanoon, J. A. K. Suykens, “Parameter estimation of delay differential equations: An integration-free LS-SVM approach,” Communications in Nonlinear Science and Numerical Simulation, Vol. 19, pp. 830-841, 2014. [PDF]
X. Huang, S. Mehrkanoon, J. A. K. Suykens, “Support vector machines with piecewise linear feature mapping,” Neurocomputing, Vol. 117, pp. 118-127, 2013. [PDF]
S. Mehrkanoon, J. A. K. Suykens, “LS-SVM approximate solution to linear time varying descriptor systems,” Automatica, 48(10), pp. 2502-2511, 2012. [PDF]
S. Mehrkanoon, T. Falck, J. A. K. Suykens, “Approximate solutions to ordinary differential equations using least squares support vector machines,” IEEE Trans. Neural Netw. Learning Syst, 23(9), pp. 1356-1367, 2012. [PDF]
S. Mehrkanoon, Z. A. Majid, M. Suleiman, K. I. Othman, Z. B. Ibrahim, “3-Point implicit block multistep method for the solution of first order ODEs,” Bull. Malays. Math. Sci. Soc, 35(2A), pp. 547-555, 2012. [PDF]
S. Mehrkanoon, “A direct variable step block multistep method for solving general third-order ODEs,” Numerical Algorithms, 57(1), pp. 53-66, 2011. [PDF]
S. Mehrkanoon, Z. A. Majid, M. Suleiman, “A variable step implicit block multistep method for solving first-order ODEs,” Journal of Computational and Applied Mathematics, 233(9), pp. 2387-2394, 2010. [PDF]
Z. A. Majid, S. Mehrkanoon, K. I. Othman, M. Suleiman, “Implementation of MPI environment for solving large systems of ODEs using block method,” WSEAS Transactions on Mathematics, 9(10), pp. 801-810, 2010. [PDF]
S. Mehrkanoon, Z. A. Majid, M. Suleiman, “Implementation of 2-point 2-step methods for the solution of first order ODEs,” Appl. Math. Sci, 4(7), pp. 305-316, 2010. [PDF]
S. Mehrkanoon, M. Suleiman, Z. A. Majid, K. I. Othman, “Parallel solution in space of large ODEs using block multistep method with step size controller,” European Journal of Scientific Research, 36(3), pp. 491-501, 2009. [PDF]
S. Mehrkanoon, M. Suleiman, Z. A. Majid, “Block method for numerical solution of fuzzy differential equations,” Int. Math. Forum, 4(46), pp. 2269-2280, 2009. [PDF]
S. Mehrkanoon, M. Suleiman, Z. A. Majid, “Spline approach to the solution of Sturm-Liouville problem,” Int. J. Contemp. Math. Sciences, 4(12), pp. 577-586, 2009.