Matin Hosseini
Cited by
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Hour-ahead solar irradiance forecasting using multivariate gated recurrent units
J Wojtkiewicz, M Hosseini, R Gottumukkala, TL Chambers
Energies 12 (21), 4055, 2019
Inception-inspired lstm for next-frame video prediction
M Hosseini, AS Maida, M Hosseini, G Raju
arXiv preprint arXiv:1909.05622, 2019
Traffic light control based on fuzzy Q-leaming
MJ Moghaddam, M Hosseini, R Safabakhsh
2015 The International Symposium on Artificial Intelligence and Signal …, 2015
Enabling interactive video streaming for public safety monitoring through batch scheduling
M Hosseini, MA Salehi, R Gottumukkala
2017 IEEE 19th International Conference on High Performance Computing and …, 2017
Learning simplified decision boundaries from trapezoidal data streams
E Beyazit, M Hosseini, A Maida, X Wu
Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018
Hierarchical predictive coding models in a deep-learning framework
M Hosseini, A Maida
arXiv preprint arXiv:2005.03230, 2020
Identification of small-signal dynamic faults in distribution systems utilizing intelligent classifiers
AJ Abianeh, M Hosseini, M Hosseini, M Barati, F Ferdowsi
2020 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2020
Fuzzy Q-learning traffic light control based on traffic flow and pedestrian number estimated from visual information
M Jalali Moghaddam, M Hosseini, R Safabakhsh
Computer and Knowledge Engineering 2 (1), 1-10, 2019
An efficient approach to breast cancer prediction based on neural network, adaboost and gaussian process
V Rafe, M Hosseini, MJ Moghaddam, R Karimi
Journal of Medical Imaging and Health Informatics 5 (3), 533-538, 2015
Inception recurrent neural network architecture for video frame prediction
M Hosseini, A Maida, S Hosseini, R Gottumukkala
SN Computer Science 4 (1), 69, 2022
Classification of emergent dynamics in microgrids utilizing an entropic complexity-based feature extractor
F Ferdowsi, M Hosseini, M Hosseini
Data-Enabled Discovery and Applications 4, 1-10, 2020
Hierarchical predictive coding models in a deep-learning framework
AS Maida, M Hosseini
arXiv preprint arXiv:2005.03230, 2020
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