Publications: Shah, Syed Afaq Ali

Journal Article

Zhang, L., Zhang, J., Shen, P., Zhu, G., Li, P., Lu, X., Zhang, H., Shah, S.A.A. and Bennamoun, M. (2020) Block level skip connections across cascaded V-Net for Multi-Organ segmentation. IEEE Transactions on Medical Imaging, 39 (9). pp. 2782-2793.

Chen, Y., Sohel, F., Shah, S.A.A. and Ding, S. (2020) Deep Boltzmann machine for corrosion classification using eddy current pulsed thermography. Optik, 219 . Art. 164828.

Zhu, G., Zhang, L., Yang, L., Mei, L., Shah, S.A.A., Bennamoun, M. and Shen, P. (2020) Redundancy and attention in convolutional LSTM for gesture recognition. IEEE Transactions on Neural Networks and Learning Systems, 31 (4). pp. 1323-1335.

Shah, S.A.A. (2020) Spatial hierarchical analysis deep neural network for RGB-D object recognition. Lecture Notes in Computer Science, 11994 . pp. 183-193.

Zhu, G., Zhang, L., Li, H., Shen, P., Shah, S.A.A. and Bennamoun, M. (2020) Topology-learnable graph convolution for skeleton-based action recognition. Pattern Recognition Letters, 135 . pp. 286-292.

Zhu, G., Zhang, L., Shen, P., Song, J., Shah, S.A.A. and Bennamoun, M. (2019) Continuous gesture segmentation and recognition using 3DCNN and convolutional LSTM. IEEE Transactions on Multimedia, 21 (4). pp. 1011-1021.

Sharif, N., White, L., Bennamoun, M., Liu, W. and Shah, S.A.A. (2019) LCEval: Learned Composite Metric for Caption Evaluation. International Journal of Computer Vision, 127 (10). pp. 1586-1610.

Shah, S.A.A., Bennamoun, M. and Molton, M. (2019) Machine Learning Approaches for Prediction of Facial Rejuvenation using Real and Synthetic Data. IEEE Access, 7 . pp. 23779-23787.

Awan, S., Bennamoun, M., Sohel, F., Shah, S.A.A., Rankin, J., Sanfilippo, F. and Dwivedi, G. (2018) Developing and testing a New Machine-Learning Method to identify patients with heart failure who are at risk of 30-Day readmission or mortality. Heart, Lung and Circulation, 27 . S91.

Zhang, L., Feng, Y., Shen, P., Zhu, G., Wei, W., Song, J., Shah, S.A.A. and Bennamoun, M. (2018) Efficient finer-grained incremental processing with MapReduce for big data. Future Generation Computer Systems, 80 . pp. 102-111.

Shah, S.A.A., Bennamoun, M., Boussaid, F. and While, L. (2018) Evolutionary feature learning for 3-D object recognition. IEEE Access, 6 . pp. 2434-2444.

Zhang, L., Xu, Q., Zhu, G., Song, J., Zhang, X., Shen, P., Wei, W., Shah, S.A.A. and Bennamoun, M. (2018) Improved colour-to-grey method using image segmentation and colour difference model for colour vision deficiency. IET Image Processing, 12 (3). pp. 314-319.

Zhang, L., Li, H., Shen, P., Zhu, G., Song, J., Shah, S.A.A. and Bennamoun, M. (2018) Improving semantic image segmentation with a probabilistic Superpixel-Based dense conditional random field. IEEE Access, 6 . pp. 15297-15310.

Zhang, L., Wang, L., Zhang, X., Shen, P., Bennamoun, M., Zhu, G., Shah, S.A.A. and Song, J. (2018) Semantic scene completion with dense CRF from a single depth image. Neurocomputing, 318 . pp. 182-195.

Shah, S.A.A., Bennamoun, M. and Boussaid, F. (2017) Keypoints-based surface representation for 3D modeling and 3D object recognition. Pattern Recognition, 64 . pp. 29-38.

Molton, M., Shah, S.A.A. and Bennamoun, M. (2016) Improving the face of cosmetic medicine: An automatic three-dimensional analysis system for facial rejuvenation. Journal of Aesthetic & Reconstructive Surgery, 2 (2).

Shah, S.A.A., Bennamoun, M. and Boussaid, F. (2016) Iterative deep learning for image set based face and object recognition. Neurocomputing, 174 . pp. 866-874.

Shah, S.A.A., Bennamoun, M. and Boussaid, F. (2016) A novel feature representation for automatic 3D object recognition in cluttered scenes. Neurocomputing, 205 . pp. 1-15.

Shah, S.A.A., Bennamoun, M. and Boussaid, F. (2015) A novel 3D vorticity based approach for automatic registration of low resolution range images. Pattern Recognition, 48 (9). pp. 2859-2871.

Conference Paper

Zhang, L., Wang, X., Li, H., Zhu, G., Shen, P., Li, P., Lu, X., Shah, S.A.A. and Bennamoun, M. (2020) Structure-Feature based Graph Self-adaptive Pooling. In: 29th International World Wide Web Conference (WWW 2020), 20 - 24 April 2020, Taipei, Taiwan

Zhang, L., Zhang, S., Shen, P., Zhu, G., Shah, S.A.A. and Bennamoun, M. (2019) Relationship detection based on object semantic inference and attention mechanisms. In: 2019 on International Conference on Multimedia Retrieval (ICMR) 2019, 10 - 13 June 2019, Ottawa ON, Canada

Zhu, G., Zhang, L., Mei, L., Shen, P., Shah, S.A.A. and Bennamoun, M. (2018) Attention in Convolutional LSTM for Gesture Recognition. In: 32nd Conference on Neural Information Processing Systems (NIPS) 2018, 3 - 8 December 2018, Montreal, Canada

Sharif, N., Bennamoun, M., White, L.R. and Shah, S.A.A. (2018) Learning-based composite metrics for improved caption evaluation. In: 56th Annual Meeting of Association for Computational Linguistics, 15 - 20 July 2018, Melbourne, Australia

Zhang, L., Kong, X., Shen, P., Zhu, G., Song, J., Shah, S.A.A. and Bennamoun, M. (2018) Reflective field for pixel-Level tasks. In: 24th International Conference on Pattern Recognition (ICPR) 2018, 20 - 24 August 2018, Beijing, China

Shah, S.A.A., Bennamoun, M. and Molton, M. (2018) A Training-Free mesh upsampling and morphing technique for 3D face rejuvenation. In: International Conference on Image and Vision Computing New Zealand (IVCNZ), 19 - 21 November 2018, Auckland, New Zealand

Shah, S.A.A., Bennamoun, M. and Molton, M. (2018) A fully automatic framework for prediction of 3D facial rejuvenation. In: International Conference on Image and Vision Computing New Zealand (IVCNZ) 2018, 19 - 21 November 2018, Auckland, New Zealand

Hu, H., Shah, S.A.A., Bennamoun, M. and Molton, M. (2017) 2D and 3D face recognition using convolutional neural network. In: IEEE Region 10 Conference (TENCON) 2017, 5 - 8 November 2017, Penang, Malaysia

Shah, S.A.A., Nadeem, U., Bennamoun, M., Sohel, F. and Togneri, R. (2017) Efficient image set classification using linear regression based image reconstruction. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2017, 21 - 26 July 2017, Honolulu, HI, USA

Zhang, L., Zhu, G., Shen, P., Song, J., Shah, S.A.A. and Bennamoun, M. (2017) Learning spatiotemporal features Using 3DCNN and Convolutional LSTM for Gesture Recognition. In: IEEE International Conference on Computer Vision Workshops (ICCVW) 2017, 22 - 29 October 2017, Venice, Italy

Shah, S.A.A., Bennamoun, M. and Boussaid, F. (2015) Automatic 3D face landmark localization based on 3D vector field analysis. In: International Conference on Image and Vision Computing New Zealand (IVCNZ) 2015, 23 - 24 November 2015, Auckland, New Zealand

Shah, S.A.A., Bennamoun, M. and Boussaid, F. (2015) A novel algorithm for efficient depth segmentation using low resolution (Kinect) images. In: IEEE 10th Conference on Industrial Electronics and Applications (ICIEA) 2015, 15 - 17 June 2015, Auckland, New Zealand

Shah, S.A.A., Bennamoun, M. and Boussaid, F. (2014) Performance evaluation of 3D local surface descriptors for low and high resolution range image registration. In: International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014, 24 - 27 November, Wollongong, NSW, Australia

Shah, S.A.A., Bennamoun, M., Boussaid, F. and El-Sallam, A.A. (2013) 3D-Div: A novel local surface descriptor for feature matching and pairwise range image registration. In: IEEE International Conference on Image Processing 2013, 15 - 18 September 2013, Melbourne, VIC

Shah, S.A.A., Bennamoun, M., Boussaid, F. and El-Sallam, A.A. (2013) Automatic object detection using objectness measure. In: 1st International Conference on Communications, Signal Processing, and their Applications (ICCSPA) 2013, 12-14 February 2013, Sharjah, United Arab Emirates

Shah, S.A.A., Bennamoun, M., Boussaid, F. and El-Sallam, A.A. (2013) A novel local surface description for automatic 3D object recognition in low resolution cluttered scenes. In: IEEE International Conference on Computer Vision Workshops 2013, 2 - 8 December 2013, Sydney, NSW

Shah, S.A.A., Yahya, K.M., Mubashar, G. and Bais, A. (2010) Quantification and visualization of MRI cartilage of the knee: A simplified approach. In: 6th International Conference on Emerging Technologies (ICET) 2010, 18 - 19 October 2010, Islamabad, Pakistan

Book Chapter

Nadeem, U., Shah, S.A.A., Sohel, F., Togneri, R. and Bennamoun, M. (2019) Deep learning for scene understanding. In: Balas, V., Roy, S., Sharma, D. and Samui, P., (eds.) Advances in Computational Intelligence. Springer, pp. 21-51.

Sharif, N., White, L., Bennamoun, M. and Shah, S.A.A. (2018) NNEval: Neural network based evaluation metric for image captioning. In: Ferrari, V., Hebert, M., Sminchisescu, C. and Weiss, Y., (eds.) Computer Vision – ECCV 2018. Springer, Cham, pp. 39-55.

Book

Khan, S., Rahmani, H., Shah, S.A.A. and Bennamoun, M. (2018) A Guide to Convolutional Neural Networks for Computer Vision. Morgan & Claypool, pp. 1-207.

Others

Nadeem, U., Shah, S.A.A., Bennamoun, M., Togneri, R. and Sohel, F. (2018) Real Time Surveillance for Low Resolution and Limited-Data Scenarios: An Image Set Classification Approach. arXiv, 1803.09470 .

Shah, S.A.A., Nadeem, U., Bennamoun, M., Sohel, F. and Togneri, R. (2017) Efficient image set classification using linear regression based image reconstruction. arXiv, 1701.02485 .