Muhammad Aminul Islam, Ph.D.
Education
B.S. in Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology
Ph.D. in Electrical and Computer Engineering, Mississippi State University
About Muhammad Aminul
Muhammad Aminul Islam received his B.Sc. degree from Bangladesh University of Engineering and Technology and Ph.D. from Mississippi State University. Currently, he is an Assistant Professor with the Department of Electrical and Computer Engineering and Computer Science at the University of New Haven, Connecticut, USA. His research interests include deep learning, computer vision, information fusion, autonomous driving, and remote sensing.
Publications
Book Chapter
D. T. Anderson, G. J. Scott, M. Islam, B. Murray, and R. Marcum, “Fuzzy choquet integration of deep convolutional neural networks for remote sensing,” in Computational Intelligence for Pattern Recognition, Springer, 2018, pp. 1–28.
Journal Articles
S. K. Kakula, A. J. Pinar, M. Islam, D. T. Anderson, and T. Havens, “Novel regularization for learning the fuzzy choquet integral with limited training data,” IEEE Transactions on Fuzzy Systems. 2020.
M. Islam, D. T. Anderson, T. C. Havens, and J. E. Ball, “A generalized fuzzy extension principle and its application to information fusion,” IEEE Transactions on Fuzzy Systems, 2020.
B. Murray, M. Islam, A. J. Pinar, D. T. Anderson, G. Scott, T. C. Havens, and J. M. Keller, “Explainable AI for the choquet integral,” IEEE Transactions on Emerging Topics in Computational Intelligence, 2020.
M. Islam, D. T. Anderson, A. J. Pinar, T. C. Havens, G. Scott, and J. M. Keller, “Enabling explainable fusion in deep learning with fuzzy integral neural networks,” Special Issue on Deep Fuzzy Models, IEEE Transactions on Fuzzy Systems, 2019, issn: 1063-6706. doi: 10.1109/TFUZZ.2019.2917124.
S. Sharma, J. E. Ball, B. Tang, D. W. Carruth, M. Doude, and M. Islam, “Semantic segmentation with transfer learning for off-road autonomous driving,” Sensors, vol. 19, no. 11, p. 2577, 2019.
M. Islam, D. T. Anderson, J. E. Ball, and N. H. Younan, “Fusion of heterogeneous bands and kernels inhyperspectral image processing,” Journal of Applied Remote Sensing, vol. 13, no. 2, 2019.
M. Islam, D. T. Anderson, F. Petry, and P. Elmore, “An efficient evolutionary algorithm to optimize the Choquet integral,” International Journal of Intelligent Systems, 2018. doi: 10.1002/int.22056.
M. Islam, D. T. Anderson, A. J. Pinar, and T. C. Havens, “Data-driven compression and efficient learning of the Choquet integral,” IEEE Transactions on Fuzzy Systems, 2017, issn: 1063-6706. doi: 10.1109/TFUZZ.2017.2755002.
Conference Articles
G. Scott, A. Hurt, A. Yang, M. Islam, D. T. Anderson, and C. Davis, “Differential morphological profile neural network for object detection in overhead imagery,” in International Joint Conference on Neural Networks, Jul. 2020.
A. Buck, D. T. Anderson, J. Keller, T. Wilkin, and M. Islam, “A weighted matrix visualization for fuzzy measures and integrals,” in IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Jul. 2020.
B. Ruprecht, W. Wu, M. Islam, D. T. Anderson, J. Keller, G. Scott, C. Davis, F. Petry, P. Elmore, K. Nock, and E. Gilmour, “Possibilistic clustering enabled neuro fuzzy logic,” in IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Jul. 2020.
C. Veal, A. Yang, A. Hurt, B. Murray, M. Islam, D. T. Anderson, G. J. Scott, T. C. Havens, J. M. Keller, and B. Tang, “Linear order statistic neuron,” in 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Jun. 2019.
B. Murray, M. Islam, A. J. Pinar, D. T. Anderson, G. J. Scott, T. C. Havens, F. Petry, and P. Elmore, “Transfer learning for the choquet integral,” in 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Jun. 2019.
W. Meadows, C. Hudson, C. Goodin, L. Dabbiru, B. Powell, M. Doude, D. Carruth, M. Islam, J. Ball, and B. Tang, “Multi-lidar placement, calibration, co-registration, and processing on a subaru forrester for off-road autonomous vehicles operations,” in Autonomous Systems: Sensors, Vehicles, Security, and the Internet of Everything, International Society for Optics and Photonics, 2019.
B. Murray, M. Islam, A. J. Pinar, T. C. Havens, D. T. Anderson, and G. Scott, “Explainable AI for understanding decisions and data-driven optimization of the Choquet integral,” in 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Jul. 2018.
M. Islam, D. T. Anderson, X. Du, T. C. Havens, and C. Wagner, “Efficient binary fuzzy measure representation and Choquet integral learning,” in 2018 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Springer, Jun. 2018.
M. Davis, L. Cagle, C. Morgan, C. Hudson, B. Shell, D. Gardner, M. Islam, C. L. Bethel, J. E. Ball, J. R. Gafford, D. T. Anderson, Y. Liu, and A. LeClair, “Hydra: a modular, universal multi-sensor data collection system,” in Autonomous Systems: Sensors, Vehicles, Security, and the Internet of Everything, International Society for Optics and Photonics, 2018.
M. Islam, D. T. Anderson, F. Petry, D. Smith, and P. Elmore, “The fuzzy integral for missing data,” in 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017, pp. 1–8.
A. J. Pinar, T. C. Havens, M. Islam, and D. T. Anderson, “Visualization and learning of the Choquet integral with limited training data,” in 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017, pp. 1–6.
D. T. Anderson, M. Islam, R. King, N. H. Younan, J. R. Fairley, S. Howington, F. Petry, P. Elmore, and A. Zare, “Binary fuzzy measures and Choquet integration for multi-source fusion,” in 2017 International Conference on Military Technologies (ICMT), 2017, pp. 676–681.
M. Islam, D. T. Anderson, J. E. Ball, and N. H. Younan, “Fusion of diverse features and kernels using lp-norm based multiple kernel learning in hyperspectral image processing,” in 2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2016, pp. 1–5.
M. Islam, D. T. Anderson, J. E. Ball, and N. H. Younan, “Clodd based band group selection,” in 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul. 2016, pp. 36–39.
M. Islam, D. T. Anderson, and T. C. Havens, “Multi-criteria based learning of the choquet integral using goal programming,” in 2015 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) held jointly with 2015 5th World Conference on Soft Computing (WConSC), 2015, pp. 1–6.