2020
Journals
- H. Zhu ; M. Guo, H. Li, Q. Wang ; A. Robles-Kelly, “Revisiting Spatio-Angular Trade-off in Light Field Camera and Extended Application in Super-Resolution”, In IEEE Transactions on Visualization and Computer Graphics, In press, 2020.
- H. Zhu ; X. Sun ; Q. Zhang ; Q. Wang ; A. Robles-Kelly ; H. Li and S. You, “Full View Optical Flow Estimation Leveraged from Light Field Superpixel”, In IEEE Transactions on Computational Imaging, Vol 6, 12-23, 2020.
- Wang, J. Ren, B. Xu, J. Li, W. Luo, and F. Xia, "MODEL: Motif-Based Deep Feature Learning for Link Prediction," In IEEE Transactions on Computational Social Systems, vol. 7, no. 2, pp. 503-516, 2020.
- Zhang, S. Sanner, M. Reda Bouadjenek, S. Gupta, “Bayesian Networks for Data Integration in the Absence of Foreign Keys”, In IEEE Transactions on Knowledge and Data Engineering, Vol 32, 803-808, 2020.
- Razzak, R. A. Saris, M. Blumenstein, G. Xu, “Integrating joint feature selection into subspace learning: A formulation of 2DPCA for outliers robust feature selection”, In Neural Networks, 121, pp.441-451, 2020.
- Khatami, A. Nazari, A. Khosravi, C. P. Lim, S. Nahavandi, “A weight perturbation-based regularisation technique for convolutional neural networks and the application in medical imaging”, In Expert Systems with Applications, 149, p. 113196, 2020.
- Nguyen, W. Luo, B. Vo, and W. Pedrycz, "Succinct contrast sets via false positive controlling with an application in clinical process redesign," In Expert Systems with Applications, vol. 161, p. 113670, 2020.
- Reda Bouadjenek, S. Sanner, Y. Du, “Relevance- and Interface-driven Clustering for Visual Information Retrieval”, In Information Systems, Vol 94, 101592, 2020.
- Gupta, D. Ko, P. Azizi, M. Reda Bouadjenek, M. Koh, A. Chong, P. C. Austin, S. Sanner., “Evaluation of Machine Learning Algorithms for Predicting Readmission after Acute Myocardial Infarction Using Routinely Collected Clinical Data”, In Canadian Journal of Cardiology, Vol 36, 878-885, 2020.
- Jiang, D. B Tay, Q. Sun, S. Ouyang, “Design of Nonsubsampled Graph Filter Banks via Lifting Schemes,” In IEEE Signal Processing Letters, Vol. 27, pp. 441-445, 2020.
- Jiang, D. B Tay, Q. Sun, S. Ouyang, “Recovery of Time-Varying Graph Signals via Distributed Algorithms on Regularized Problems,” In IEEE Transactions on Signal and Information Processing over Networks, Vol. 6, pp. 540-555, 2020.
- B. Tay and J. Jiang, "Time-Varying Graph Signal Denoising via Median Filters," In IEEE Transactions on Circuits and Systems II: Express Briefs, In Press, 2020.
Conferences
- Ma, H. Huang, Y. Wang, S. Romano, S. Erfani, J. Bailey, "Normalized Loss Functions for Deep Learning with Noisy Labels", In International Conference on Machine Learning, 2020.
- Wu, Y. Wang, S.-T. Xia, J. Bailey and X. Ma, "Skip Connections Matter: on the Transferability of Adversarial Examples Generated with ResNets", In International Conference on Learning Representations, 2020.
- Wang, D. Zou, J. Yi, J. Bailey, X. Ma and Q. Gu, "Improving Adversarial Robustness Requires Revisiting Misclassified Examples", In International Conference on Learning Representations, 2020.
- Y. Koh, D. T. Nguyen, Q.-T. Truong, “Alexander Binder, and Sai-Kit Yeung. SideInfNet: a deep neural network for semi-automatic semantic segmentation with side information”, In European Conference on Computer Vision, 2020.
- -H. Pham, M. A. Uy, B.-S. Hua, D. T. Nguyen, Gemma Roig, and Sai-Kit Yeung, “LCD: learned cross-domain descriptors for 2D-3D matching”, In AAAI 2020.
- M. Khan, S. S. Naqvi, M. Arsalan, M. A. Khan, H. A. Khan, A. Haider, ”Exploiting Residual Edge Information in Deep Fully Convolutional Neural Networks For Retinal Vessel Segmentation”, In International Joint Conference on Neural Networks, 2020.
- M. Khan, F. Abdullah, S. S. Naqvi, M. Arsalan, M. A. Khan, “Shallow Vessel Segmentation Network for Automatic Retinal Vessel Segmentation”, In International Joint Conference on Neural Networks, 2020.
- Luo, A. Mashrur, A. Robles-Kelly, and G. Li, "Bias-regularised neural- network metamodelling of insurance portfolio risk," In International Joint Conference on Neural Networks, 2020.
- M. Shoeiby, L. Petersson, A. Armin, S. Aliakbarian and A. Robles-Kelly, “Super-resolved Chromatic Mapping of Snapshot Mosaic Image Sensors via a Texture Sensitive Residual Network”, In Winter Conference on Applications of Computer Vision, IEEE Computer Society, 2020
- Razzak, K. Zafar, M. Imran, G. Xu, “Randomized nonlinear one-class support vector machines with bounded loss function to detect of outliers for large scale IoT data”, In Future Generation Computer Systems,
- Z. Saeed, R. A. Abbasi, I. Razzak, “EveSense: What Can You Sense from Twitter?”, In European Conference on Information Retrieval, pp. 491-495, 2020.
2019
Journals
- Saeed, RA Abbasi, MI Razzak, G Xu, Event Detection in Twitter Streams using Weighted Dynamic Heartbeat Graph Approach, IEEE Computational Intelligence Magazine, 1-14
- Naseer, M. Rani, S. Naz, I. Razzak, G. Xu,”Refining Parkinson’s neurological disorder identification through deep transfer learning”, In Neural Computing and Applications, 32(3), pp.839-854,2019.
- Razzak, M. Imran, G. Xu, G., “Efficient brain tumor segmentation with multiscale two-pathway-group conventional neural networks”, In IEEE journal of biomedical and health informatics, 23(5), pp.1911-1919, 2019
- Khawaja, T. M. Khan, K. Naveed, S. S. Naqvi, N. U. Rehman, S. J. Nawaz, “An Improved Retinal Vessel Segmentation Framework Using Frangi Filter Coupled with the Probabilistic Patch Based Denoiser”, In IEEE Access, Vol 7, 164344-164361, 2019.
- Aslam, T. M. Khan, S. S. Naqvi, G. Holmes, R. Naffa, “CDED-NetOn the Application of Automated Machine Vision for Leather Defect Inspection and Grading: A Survey”, In IEEE Access, Vol 7, 176065-176086, 2019
- M. Khan, D. G. Bailey, M. A. U. Khan, Y. Kong, “Real Time Implementation of Fast Iris Segmentation on FPGA”, In Journal of Real-Time Image Processing, 2019.
- V. Chandrasekara, C.D. Tilakaratne, M.A. Mammadov, “An Improved Probabilistic Neural Network Model for Directional Prediction of a Stock Market Index”, In Applied Sciences 9 (24), 5334, 2019.
- Y. Duan, L.M. Wang, M. Mammadov, H. Lou, M.H. Sun, “Discriminatory Target Learning: Mining Significant Dependence Relationships from Labeled and Unlabeled Data”, In Entropy 21 (5), 537, 2019.
- Wang, Y. Liu, M. Mammadov, M. Sun, S. Qi, “Discriminative Structure Learning of Bayesian Network Classifiers from Training Dataset and Testing Instance”, In Entropy 21 (5), 489, 2019.
- Reda Bouadjenek, J. Zobel, K. Verspoor, “Automated Assessment of Biological Database Assertions Using the Scientific Literature”, In BMC Bioinformatics, Vol 20, 216, 2019.
- Wang, G. Wu, M. Reda Bouadjenek, S. Sanner, “A Novel Regularizer for Temporally Stable Learning with an Application to Twitter Topic Classification”, In The SIAM International Conference on Data Mining (SDM), 217-225, 2019.
- Mohamed Reda Bouadjenek, Hakim Hacid, Mokrane Bouzeghoub, “Personalized Social Query Expansion Using Social Annotations”, In Transactions on Large-Scale Data- and Knowledge-Centered Systems, Vol 11360, 1-25, 2019.
- B. Tay, A. Ortega, ”M-channel graph filter banks: Polyphase analysis and structures,” in IEEE Signal Processing Letters, Vol. 26, No. 5, pp. 730-734, May 2019.
- J. Jiang, D. B Tay, “Decentralised signal processing on graphs via matrix inverse approximation,” In Signal processing, Vol. 165, pp. 292-302, Dec 2019.
Conferences
- Wang, X. Ma, J. Bailey, J. Yi, B. Zhou, Q. Gu, "On the Convergence and Robustness of Adversarial Training", In International Conference on Machine Learning, 2019.
- Vu, T. D. Nguyen, T. Le, W. Luo, and D. Q. Phung, "Robust Anomaly Detection in Videos Using Multilevel Representations," In AAAI, 2019.
- Wang, X. Ma, Z. Chen, Y. Luo, J. Yi, J. Bailey, "Symmetric Cross Entropy for Robust Learning with Noisy Labels", In IEEE International Conference on Computer Vision and Pattern Recognition, 2019.
- -H. Pham, D. T. Nguyen, B.-S. Hua, G. Roig, S.-K. Yeung, “JSIS3D: Joint semantic-instance segmentation of 3D point clouds with multi-task pointwise networks and multi-value conditional random fields”, In IEEE International Conference on Computer Vision and Pattern Recognition, 2019.
- A. Uy, Q.-H. Pham, B.-S. Hua, D. T. Nguyen, S.-K. Yeung, “Revisiting point cloud classification: a new benchmark dataset and classification model on real-world data”, In IEEE International Conference on Computer Vision, 2019.
- Li, A. Robles-Kelly, S. You and Y. Matsushita, “Learning to Minify Photometric Stereo”, In IEEE International Conference on Computer Vision and Pattern Recognition, 2019.
- Ge, X. Fuy, N. Syedz, Z. Baig, G. Teox and A. Robles-Kelly, “Deep Learning-based Intrusion Detection for IoT Networks”, In Pacific Rim International Symposium on Dependable Computing, 2019.
- Li, J. Qi, R. Zhang, X. Ma, R. Kotagiri, "Generative Image Inpainting with Submanifold Alignment", In International Joint Conference on Artificial Intelligence, 2019.
- Imran Razzak, Tariq M. Khan, “One-Class Support Tensor Machines with Bounded Hinge Loss Function for Anomaly Detection”, In International Joint Conference on Neural Networks, 2020.
- Robles-Kelly, A. Nazari, “Incorporating the Barzilai-Borwein Adaptive Step Size into Sugradient Methods for Deep Network Training”, In Digital Image Computing: Techniques and Applications, p.1-6, 2019.
- Khatami, P. M. Kebria, S. M. Jalali,, A. Khosravi, A. Nazari, M. Shamszadeh, T. Nguyen, S. Nahavandi, “A GA-Based Pruning Fully Connected Network for Tuned Connections in Deep Networks” In IEEE International Conference on Systems, Man and Cybernetics, pp. 3492-3497, 2019.
- Lucas, A. Shifaz, C. Pelletier, L. Neil, N. Zaidi, B. Goethals, F. Petitjean, G. Webb, Proximity Forest: An effective and Scalable Distance-based Classifier for Time Series, In Data Mining and Knowledge Discovery, Volume 33, pages 607-635, 2019
- Nguyen, W. Luo, T. D. Nguyen, S. Venkatesh, and D. Phung, "Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint," In Machine Learning and Knowledge Discovery in Databases, 2019.