2024
M. H. M. Noor, A. O. Ige, “A Survey on Deep Learning and State-of-the-art Applications”, arXiv preprint, Mar. 2024. doi, pdf
M. N. A. Wahab, A. Nazir, A. Khalil, J. H. Wong, M. F. Akbar, M. H. M. Noor, A. S. A. Mohamed, “Improved Genetic Algorithm for Mobile Robot Path Planning in Static Environments”, Expert Systems with Applications, vol. pp. Mar. 2024. doi, pdf
S. C. Tay, M. N. A. Wahab, A. S. A. Mohamed, M. H. M. Noor, B. K. Khaw, L. C. Lim, W. J. B. Liau, “Enhancing EfficientNet-YOLOv4 for Integrated Circuit Detection on Printed Circuit Board”, IEEE Access, vol. pp., Jan. 2024. doi, pdf
S. Tijjani, M. N. A. Wahab, M. H. M. Noor, “An enhanced particle swarm optimization with position update for optimal feature selection”, Expert Systems with Applications, vol. , pp. , Jan. 2024. doi, pdf
2023
A. O. Ige, M. H. M. Noor, “A Deep Local-Temporal Architecture with Attention for Lightweight Human Activity Recognition”, Applied Soft Computing, vol. 149, pp. 110954, Oct. 2023. doi, pdf
T. A. Al-Qablan, M. H. M. Noor, M. A. Al-Betar and A. T. Khader, “A Survey on Sentiment Analysis and Its Applications”, Neural Computing and Applications, vol. 35, pp. 21567-21601, Aug. 2023. doi, pdf
A. Baraka, M. H. M. Noor, “Similarity Segmentation Approach for Sensor-based Activity Recognition”, IEEE Sensors Journal, vol. 23, pp. 19704-19716, Jul. 2023. doi, read
T. Zhonglin, M. N. A. Wahab, M. F. Akbar, A. S. A. Mohamed, M. H. M. Noor, B. A. Rosdi, “SFFSORT Multi-Object Tracking by Shallow Feature Fusion for Vehicle Counting”, IEEE Access, vol. 11, pp. 76827-76841, Jul 2023, doi
N. Nordin, Z. Zainol, M. H. M. Noor, L. F. Chan, “An Ontology-based Modeling for Classifying Risk of Suicidal Behavior”, 12th International Conference on Software and Computer Applications (ICSCA2023), 2023, doi
F. S. E. Shaninah, M. H. M. Noor, “The impact of big five personality trait in predicting student academic performance”, Journal of Applied Research in Higher Education, vol. , pp. , Jul. 2023. doi
T. A. Al-Qablan, M. H. M. Noor, M. A. Al-Betar and A. T. Khader, “Improved Binary Gray Wolf Optimizer Based on Adaptive β-Hill Climbing for Feature Selection”, IEEE Access, vol. 11, pp. 59866-59881, Jun. 2023. doi
A. O. Ige, N. K. Tomar, F. O. Aranuwa, O. Oriola, A. O. Akingbesote, M. H. M. Noor, M. Mazzara, B. Aribisala, “ConvSegNet: Automated Polyp Segmentation from Colonoscopy using Context Feature Refinement with Multiple Convolutional Kernel Sizes”, IEEE Access, vol. 11, pp. 16142–16155, Feb. 2023. doi
2022
A. O. Ige, M. H. M. Noor, “A Lightweight Deep Learning with Feature Weighting for Activity Recognition”, Computational Intelligence, vol. 39, pp. 315–343, Dec. 2022. doi, pdf
H. Abdu, M. H. M. Noor, “A Survey on Waste Detection and Classification using Deep Learning”, IEEE Access, vol. 10, pp. 128151-128165, Dec. 2022. doi, pdf
N. Nordin, Z. Zainol, M. H. M. Noor, L. F. Chan, “An Explainable Predictive Model for Suicide Attempt Risk using An Ensemble Learning and Shapley Additive Explanations (SHAP) Approach”, Asian Journal of Psychiatry, vol. 79, pp. 103316, Nov. 2022. doi, pdf
A. O. Ige, M. H. M. Noor, “Unsupervised Feature Learning in Activity Recognition using Convolutional Denoising Autoencoders with Squeeze and Excitation Networks”, 5th International Conference on Information and Communications Technology (ICOIACT), 2022, doi
H. Abdu, M. H. M. Noor, “Domestic Trash Classification with Transfer Learning Using VGG16”, IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE2022), 2022, doi, pdf
N. Nordin, Z. Zainol, M. H. M. Noor, L. F. Chan, “Explainable Machine Learning Models for Suicidal Behavior Prediction”, 6th International Conference on Medical and Health Informatics (ICMHI2022), 2022, pp. 118 – 123. doi, pdf
A. O. Jimale, M. H. M. Noor, “Fully Connected Generative Adversarial Network For Human Activity Recognition”, IEEE Access, vol. 10, pp. 100257-100266, Sep. 2022. doi, pdf
N. Nordin, Z. Zainol, M. H. M. Noor, L. F. Chan, “Suicidal Behaviour Prediction Models using Machine Learning Techniques: A Systematic Review”, Artificial Intelligence in Medicine, vol. 132, pp. 102395, Sep. 2022. doi, pdf
A. O. Ige, M. H. M. Noor, “A Survey on Unsupervised Learning for Wearable Sensor-based Activity Recognition”, Applied Soft Computing, vol. 127, pp. 109363, Jul. 2022. doi, pdf, read
M. H. M. Noor, S. Y. Tan, M. N. A. Wahab, “Deep Temporal Conv-LSTM for Activity Recognition”, Neural Processing Letters, vol. 54, pp. 4027–4049, Mar. 2022. doi, pdf, read, code
A. Baraka, M. H. M. Noor, “Weakly-supervised Temporal Action Localization: A Survey”, Neural Computing and Applications, vol. 34, pp. 8479–8499, Mar. 2022. doi, pdf, read
2021
M. N. A. Wahab, A. T. Z. Ren, A. Nazir, M. H. M. Noor, M. F. Akbar and A. S. A. Mohamed, “EfficientNet-Lite and Hybrid CNN-KNN Implementation for Facial Expression Recognition on Raspberry Pi”, IEEE Access, vol. 9, pp. 134065-134080, Sep. 2021. doi
A. O. Jimale, M. H. M. Noor, “Subject Variability in Sensor-based Activity Recognition”, Journal of Ambient Intelligence and Humanized Computing, vol. , pp. , Sep. 2021. doi, pdf, read
M. H. M. Noor, A. Nazir, M. N. A. Wahab, J. Y. L, Ooi, “Detection of Freezing of Gait using Unsupervised Convolutional Denoising Autoencoder”, IEEE Access, vol. 9, pp. 115700-115709, Aug. 2021. doi
H. Abdu, M. H. M. Noor, R. Abdullah, “An Efficient Multi-sensor Positions Human Activity Recognition: Elderly Peoples in Rural Areas in Focus”, International Conference on Emerging Applications and Technologies for Industry 4.0 (EATI’2020), 2020. Lecture Notes in Networks and Systems, vol. 254. doi
M. Aminu, N. A. Ahmad, M. H. M. Noor “Covid-19 Detection via Deep Neural Network and Occlusion Sensitivity Maps”, Alexandria Engineering Journal, vol. 60, pp. 4829-4855, Oct. 2021. doi, pdf
N. Nordin, Z. Zainol, M. H. M. Noor, L. F. Chan, “A Comparative Study of Machine Learning Techniques for Suicide Attempts Predictive Model”, Health Informatics Journal, vol. 27, Issue 1, pp. 1-16, 2021. doi, pdf
M. H. M. Noor, “Feature Learning using Convolutional Denoising Autoencoder for Activity Recognition”, Neural Computing and Applications, vol. 33, pp. 10909–10922, Sep. 2021. doi, pdf, read, code
2020
M. H. Chan, M. H. M. Noor, “A Unified Generative Model using Generative Adversarial Network for Activity Recognition”, Journal of Ambient Intelligence and Humanized Computing, vol. 12, pp. 8119–8128, Jul. 2021. doi, pdf, read
2019
M. H. M. Noor, M. A. Ahmadon, M. K. Osman, “Activity Recognition using Deep Denoising Autoencoder,” 2019 9th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), 2019, pp. 188 – 192. doi, pdf
N. A. M. Yusof, A. Ibrahim, M. H. M. Noor, N. M. Tahir, N. M. Yusof, N. Z. Abidin M. K. Osman, “Deep Convolution Neural Network for Crack Detection on Asphalt Pavement,” Journal of Physics: Conference Series, Vol. 1349. No. 1. IOP Publishing, 2019. doi, pdf
N. A. M. Yusof, M. K. Osman, Z. Hussain, M. H. M. Noor, A. Ibrahim, N. M. Tahir, N. Z. Abidin, “Automated Asphalt Pavement Crack Detection and Classification using Deep Convolution Neural Network,” 2019 9th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), 2019, pp. 215 – 220. doi
2018
N. A. M. Yusof ; M. K. Osman ; M. H. M. Noor ; A. Ibrahim ; N. M. Tahir ; N. M. Yusof , “Crack Detection and Classification in Asphalt Pavement Images using Deep Convolution Neural Network,” 2018 8th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), 2018, pp. 227 – 232. doi
M. H. M. Noor, Z. Salcic, and K. I.-K. Wang, “Ontology-based Sensor Fusion Activity Recognition”, Journal of Ambient Intelligence and Humanized Computing, vol. 11, Issue 8, pp. 3073–3087, Jan. 2018. doi, pdf
2017 and older
M. H. M. Noor, Z. Salcic, and K. I.-K. Wang, “Adaptive Sliding Window Segmentation for Physical Activity Recognition using a Single Tri-axial Accelerometer”, Pervasive and Mobile Computing, vol. 38, Part 1, pp. 41–59, Jul. 2017. doi, pdf
M. H. M. Noor, Z. Salcic, and K. I.-K. Wang, “Enhancing Ontological Reasoning with Uncertainty Handling for Activity Recognition”, Knowledge-Based Systems, vol. 114, pp. 47–60, Dec. 2016. doi, pdf
M. H. M. Noor, Z. Salcic, and K. I.-K. Wang, “Dynamic Sliding Window Method for Physical Activity Recognition using a Single Tri-axial Accelerometer”, in 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA), 2015, pp. 102–107. doi