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ORCIDM. M. Manjurul Islam
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2020 – today
- 2024
[j10]M. M. Manjurul Islam
, Jong-Myon Kim:
Time-frequency envelope analysis-based sub-band selection and probabilistic support vector machines for multi-fault diagnosis of low-speed bearings. J. Ambient Intell. Humaniz. Comput. 15(2): 1527-1542 (2024)- [c7]M. M. Manjurul Islam, Md. Alamgir Kabir, Alamin Sheikh, Muhammad Saiduzzaman, Abdelakram Hafid, Saad Abdullah:
Enhancing Speech Emotion Recognition Using Deep Convolutional Neural Networks. ICMLT 2024: 95-100 - 2023
- [j9]Md. Alamgir Kabir, Atiq ur Rehman, M. M. Manjurul Islam, Nazakat Ali, Marcia Lourenco Baptista:
Cross-Version Software Defect Prediction Considering Concept Drift and Chronological Splitting. Symmetry 15(10): 1934 (2023) - 2022
- [j8]Md Junayed Hasan, M. M. Manjurul Islam, Jong-Myon Kim:
Bearing Fault Diagnosis Using Multidomain Fusion-Based Vibration Imaging and Multitask Learning. Sensors 22(1): 56 (2022) - [c6]Md. Alamgir Kabir, M. M. Manjurul Islam, S. M. Hasan Mahmud, Md. Fazla Elahe:
Spectrum Impact Analysis of Fault Proneness Statement for Improved Fault Localization. ICCA 2022: 59-66
2010 – 2019
- 2019
- [j7]Alexander E. Prosvirin, M. M. Manjurul Islam, Jong-Myon Kim:
An Improved Algorithm for Selecting IMF Components in Ensemble Empirical Mode Decomposition for Domain of Rub-Impact Fault Diagnosis. IEEE Access 7: 121728-121741 (2019) - [j6]M. M. Manjurul Islam, Jong-Myon Kim:
Automated bearing fault diagnosis scheme using 2D representation of wavelet packet transform and deep convolutional neural network. Comput. Ind. 106: 142-153 (2019) - [j5]M. M. Manjurul Islam, Jong-Myon Kim:
Reliable multiple combined fault diagnosis of bearings using heterogeneous feature models and multiclass support vector Machines. Reliab. Eng. Syst. Saf. 184: 55-66 (2019) - [j4]Wasim Ahmad, Sheraz Ali Khan, M. M. Manjurul Islam, Jong-Myon Kim:
A reliable technique for remaining useful life estimation of rolling element bearings using dynamic regression models. Reliab. Eng. Syst. Saf. 184: 67-76 (2019) - [j3]M. M. Manjurul Islam, Jong-Myon Kim:
Vision-Based Autonomous Crack Detection of Concrete Structures Using a Fully Convolutional Encoder-Decoder Network. Sensors 19(19): 4251 (2019) - 2018
- [j2]Alexander E. Prosvirin, M. M. Manjurul Islam, Jaeyoung Kim, Jong-Myon Kim:
Rub-Impact Fault Diagnosis Using an Effective IMF Selection Technique in Ensemble Empirical Mode Decomposition and Hybrid Feature Models. Sensors 18(7): 2040 (2018) - [j1]M. M. Manjurul Islam, Muhammad Sohaib, Jaeyoung Kim, Jong-Myon Kim:
Crack Classification of a Pressure Vessel Using Feature Selection and Deep Learning Methods. Sensors 18(12): 4379 (2018) - [c5]M. M. Manjurul Islam, Jong-Myon Kim:
Motor Bearing Fault Diagnosis Using Deep Convolutional Neural Networks with 2D Analysis of Vibration Signal. Canadian AI 2018: 144-155 - [c4]M. M. Manjurul Islam, Alexander E. Prosvirin, Jong-Myon Kim:
Intelligent Rub-Impact Fault Diagnosis Based on Genetic Algorithm-Based IMF Selection in Ensemble Empirical Mode Decomposition and Diverse Features Models. IDEAL (1) 2018: 147-155 - [c3]Se-Jong Kang, Jae-Young Kim, In-Kyu Jeong, M. M. Manjurul Islam, Kichang Im, Jong-Myon Kim:
An Improved Gas Classification Technique Using New Features and Support Vector Machines. SoCPaR 2018: 158-166 - 2017
- [c2]M. M. Manjurul Islam, Md. Rashedul Islam, Jong-Myon Kim:
A Hybrid Feature Selection Scheme Based on Local Compactness and Global Separability for Improving Roller Bearing Diagnostic Performance. ACALCI 2017: 180-192 - 2015
- [c1]M. M. Manjurul Islam, Sheraz A. Khan, Jong-Myon Kim:
Multi-fault Diagnosis of Roller Bearings Using Support Vector Machines with an Improved Decision Strategy. ICIC (3) 2015: 538-550
Coauthor Index
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