Facial expression recognition using a hybrid CNN–SIFT aggregator T Connie, M Al-Shabi, WP Cheah, M Goh International workshop on multi-disciplinary trends in artificial …, 2017 | 179 | 2017 |
Lung nodule classification using deep local–global networks M Al-Shabi, BL Lan, WY Chan, KH Ng, M Tan International journal of computer assisted radiology and surgery 14, 1815-1819, 2019 | 88 | 2019 |
Gated-Dilated Networks for Lung Nodule Classification in CT Scans M Al-Shabi, HK Lee, M Tan IEEE Access 7, 178827 - 178838, 2019 | 54 | 2019 |
ProCAN: Progressive growing channel attentive non-local network for lung nodule classification M Al-Shabi, K Shak, M Tan Pattern Recognition 122, 108309, 2022 | 48 | 2022 |
3D axial-attention for lung nodule classification M Al-Shabi, K Shak, M Tan International journal of computer assisted radiology and surgery 16 (8 …, 2021 | 25 | 2021 |
Classification of tuberculosis with SURF spatial pyramid features FHO Alfadhli, AA Mand, MS Sayeed, KS Sim, M Al-Shabi 2017 International conference on robotics, automation and sciences (ICORAS), 1-5, 2017 | 22 | 2017 |
Smart content recognition from images using a mixture of convolutional neural networks T Connie, M Al-Shabi, M Goh IT Convergence and Security 2017: Volume 1, 11-18, 2017 | 21 | 2017 |
Cribriform pattern detection in prostate histopathological images using deep learning models M Singh, EM Kalaw, W Jie, M Al-Shabi, CF Wong, DM Giron, KT Chong, ... arXiv preprint arXiv:1910.04030, 2019 | 8 | 2019 |
Comparison of two-dimensional synthesized mammograms versus original digital mammograms: A quantitative assessment M Tan, M Al-Shabi, WY Chan, L Thomas, K Rahmat, KH Ng Medical & biological engineering & computing 59, 355-367, 2021 | 5 | 2021 |
A new semi-supervised self-training method for lung cancer prediction K Shak, M Al-Shabi, A Liew, BL Lan, WY Chan, KH Ng, M Tan arXiv preprint arXiv:2012.09472, 2020 | 5 | 2020 |
Lung Nodule Classification Using Scale-Invariant Neural Networks M Al-Shabi Monash University, 2021 | | 2021 |