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• Article

  Machine learning-based prediction of heart failure readmission or death: implications of choosing the right model and the right metrics

  Awan, S. E., Bennamoun, M., Sohel, F., Sanfilippo, F. M. & Dwivedi, G., 1 Apr 2019, In : ESC Heart Failure. 6, 2, p. 428-435 8 p.

  Research output: Contribution to journal › Article

  Open Access

  • Machine Learning
  • Area Under Curve
  • Heart Failure
  • Neural Networks (Computer)
  • Sensitivity and Specificity
  10 Citations (Scopus)

• Nature-inspired techniques in the context of fraud detection

  Behdad, M., Barone, L., Bennamoun, M. & French, T., 2012, In : IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews. 42, 6, p. 1273 - 1290

  Research output: Contribution to journal › Article
  38 Citations (Scopus)

• NormalNet: A voxel-based CNN for 3D object classification and retrieval

  Wang, C., Cheng, M., Sohel, F., Bennamoun, M. & Li, J., 5 Jan 2019, In : Neurocomputing. 323, p. 139-147 9 p.

  Research output: Contribution to journal › Article
  26 Citations (Scopus)

• NSCT-based fusion method for forward-looking sonar image mosaic

  Zhang, J., Sohel, F., Bennamoun, M., Bian, H. & An, S., 1 Oct 2017, In : IET Radar, Sonar and Navigation. 11, 10, p. 1512-1522 11 p.

  Research output: Contribution to journal › Article

  Open Access

  File

  • Sonar
  • Image fusion
  • Pixels
  • Experiments
  5 Citations (Scopus)

  328 Downloads (Pure)

• On principal component analysis for high-dimensional XCSR

  Behdad, M., French, T., Barone, L. & Bennamoun, M., 2012, In : Evolutionary Intelligence. 5, p. 129-138

  Research output: Contribution to journal › Article
  5 Citations (Scopus)

• Ontology Learning from Text: A look back and into the future

  Wong, W. Y., Liu, W. & Bennamoun, M., 2012, In : ACM Computing Surveys. 44, 4, p. 1-36

  Research output: Contribution to journal › Article
  221 Citations (Scopus)

• On XCSR for electronic fraud detection

  Behdad, M., Barone, L., French, T. & Bennamoun, M., 2012, In : Evolutionary Intelligence. 5, p. 139-150

  Research output: Contribution to journal › Article
  11 Citations (Scopus)

• Partial fingerprint indexing: a combination of local and reconstructed global features

  Zhou, W., Hu, J., Wang, S., Petersen, I. & Bennamoun, M., 2015, In : CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE. N/A, p. 1-18

  Research output: Contribution to journal › Article
  5 Citations (Scopus)

• Quantitative error analysis of bilateral filtering

  An, S., Boussaïd, F., Bennamoun, M. & Sohel, F., 2015, In : IEEE Signal Processing Letters. 22, 2, p. 202-206

  Research output: Contribution to journal › Article

  • Quantitative Analysis
  • Filtering
  • Error Analysis
  • Error analysis
  • Interpolation
  5 Citations (Scopus)

• RAFP-Pred: Robust Prediction of Antifreeze Proteins using Localized Analysis of n-Peptide Compositions

  Khan, S., Naseem, I., Togneri, R. & Bennamoun, M., 2018, In : IEEE/ACM Transactions on Computational Biology and Bioinformatics. 15, 1, p. 244-250

  Research output: Contribution to journal › Article

  • Antifreeze Proteins
  • prednylidene
  • Peptides
  • Protein
  • Proteins
  10 Citations (Scopus)

• ResFeats: Residual network based features for underwater image classification

  Mahmood, A., Bennamoun, M., An, S., Sohel, F. & Boussaid, F., 1 Nov 2019, In : Image and Vision Computing. 103811.

  Research output: Contribution to journal › Article

  • Aquatic ecosystems
  • Deep neural networks
  • Image classification
  • Imaging systems
  • Deep learning
  7 Citations (Scopus)

• Review of Modelling and Simulating Crowds at Mass Gathering Events: Hajj as a Case Study

  Owaidah, A., Olaru, D., Bennamoun, M., Sohel, F. & Khan, N., 31 Mar 2019, In : JASSS. 22, 2, 36 p., 9.

  Research output: Contribution to journal › Article

  Open Access
  3 Citations (Scopus)

• RGB-D Object Recognition and Grasp Detection Using Hierarchical Cascaded Forests

  Asif, U., Bennamoun, M. & Sohel, F., Jun 2017, In : IEEE Transactions on Robotics. 33, 3, p. 547-564

  Research output: Contribution to journal › Article

  Open Access

  File

  • Object recognition
  • Convolution
  • Labels
  • Robotics
  • Uncertainty
  50 Citations (Scopus)

  916 Downloads (Pure)

• Robust regression for face recognition

  Naseem, I., Togneri, R. & Bennamoun, M., 2012, In : Pattern Recognition. 45, 1, p. 104-118

  Research output: Contribution to journal › Article

  • Linear regression
  • Face recognition
  • Lighting
  • Pixels
  • Speckle
  103 Citations (Scopus)

• Scale space clustering evolution for salient region detection on 3D deformable shapes

  Wang, X., Sohel, F., Bennamoun, M., Guo, Y. & Lei, H., 1 Nov 2017, In : Pattern Recognition. 71, p. 414-427 14 p.

  Research output: Contribution to journal › Article
  10 Citations (Scopus)

• Semantic scene completion with dense CRF from a single depth image

  Zhang, L., Wang, L., Zhang, X., Shen, P., Bennamoun, M., Zhu, G., Shah, S. A. A. & Song, J., 27 Nov 2018, In : Neurocomputing. 318, p. 182-195 14 p.

  Research output: Contribution to journal › Article

  • Semantics
  • Robots
  • Linear Programming
  • Datasets
  • Linear programming
  7 Citations (Scopus)

• Single image dehazing using deep neural networks

  Hodges, C., Bennamoun, M. & Rahmani, H., 1 Dec 2019, In : Pattern Recognition Letters. 128, p. 70-77 8 p.

  Research output: Contribution to journal › Article

  • Deep neural networks
  • Deep learning
  • Network performance
  • Network architecture
  • Computer vision
  9 Citations (Scopus)

• SkeletonNet: Mining Deep Part Features for 3-D Action Recognition

  Ke, Q., An, S., Bennamoun, M., Sohel, F. & Boussaid, F., 2017, In : IEEE Signal Processing Letters. p. 731-735

  Research output: Contribution to journal › Article

  Open Access

  File

  • Action Recognition
  • Mining
  • Skeleton
  • 3D
  • Deep learning
  83 Citations (Scopus)

  789 Downloads (Pure)

• Sliding-Window Designs for Vertex-based Shape Coding

  Sohel, F., Karmakar, G. C., Dooley, L. S. & Bennamoun, M., 2012, In : IEEE Transactions on Multimedia. 14, 3, p. 683-692

  Research output: Contribution to journal › Article

  7 Citations (Scopus)

• Spatially optimized data-level fusion of texture and shape for face recognition

  Al-Osaimi, F. R., Bennamoun, M. & Mian, A., 11 Aug 2012, In : IEEE Transactions on Image Processing. 21, 2, p. 859-872

  Research output: Contribution to journal › Article

  • Face recognition
  • Fusion reactions
  • Textures
  • Lighting
  • Pixels
  46 Citations (Scopus)

• The most discriminant subbands for face recognition: A novel information-theoretic framework

  Alim, A., Naseem, I., Togneri, R. & Bennamoun, M., 1 Sep 2018, In : International Journal of Wavelets, Multiresolution and Information Processing. 16, 5, 1850040.

  Research output: Contribution to journal › Article

  • Face Recognition
  • Discriminant
  • Face recognition
  • Face
  • Framework
  1 Citation (Scopus)

• Three-dimensional scanning for measurement of bulk density in gravelly soils

  Scanlan, C. A., Rahmani, H., Bowles, R. & Bennamoun, M., 1 Sep 2018, In : Soil Use and Management. 34, 3, p. 380-387 8 p.

  Research output: Contribution to journal › Article

  Open Access

  • gravelly soils
  • bulk density
  • casts (medical)
  • void
  • Soils
  1 Citation (Scopus)
• Book

  3D Shape Analysis: Fundamentals, Theory, and Applications

  Laga, H., Guo, Y., Tabia, H., Fisher, R. & Bennamoun, M., 2019, Wiley-Blackwell. 368 p.

  Research output: Book/Report › Book

• A Guide to Convolutional Neural Networks for Computer Vision

  Khan, S., Rahmani, H., Shah, S. A. A. & Bennamoun, M., 2018, Morgan & Claypool Publishers. 207 p. (Synthesis Lectures on Computer Vision; vol. 8, no. 1)

  Research output: Book/Report › Book

  • Computer vision
  • Neural networks
  • Image classification
  • Sports medicine
  • Network layers

• Neural Representations of Natural Language

  White, L., Togneri, R., Liu, W. & Bennamoun, M., 2018, 1 ed. Austria: Springer. 122 p. (Studies in Computational Intelligence; vol. 783)

  Research output: Book/Report › Book

  • Neural networks
  • Recurrent neural networks
  • Byproducts
• Chapter

  Computer Vision for Human-Machine Interaction

  Ke, Q., Liu, J., Bennamoun, M., An, S., Sohel, F. & Boussaid, F., 2018, Computer Vision for Assistive Healthcare. Marco, L. & Farinella, G. M. (eds.). Academic Press, p. 127-145

  Research output: Chapter in Book/Conference paper › Chapter

  • Gesture recognition
  • Computer vision
  • Deep learning
  • User interfaces
  • Neural networks
  14 Citations (Scopus)

• Deep Learning for Coral Classification

  Mahmood, A., Bennamoun, M., An, S., Sohel, F., Boussaid, F., Hovey, R., Kendrick, G. & Fisher, R., 2017, Handbook of Neural Computation. Samui, P., Roy, S. S. & Balas, V. E. (eds.). London: Academic Press, p. 383-401

  Research output: Chapter in Book/Conference paper › Chapter

  14 Citations (Scopus)

• Deep learning for driverless vehicles

  Hodges, C., An, S., Rahmani, H. & Bennamoun, M., 1 Jan 2019, Smart Innovation, Systems and Technologies. Springer Science + Business Media, Vol. 136. p. 83-99 17 p. (Smart Innovation, Systems and Technologies; vol. 136).

  Research output: Chapter in Book/Conference paper › Chapter

  • Deep Learning
  • Autonomous Vehicles
  • Deep learning
  • Automation
  • Autonomous vehicles
  2 Citations (Scopus)

• Deep learning for marine species recognition

  Xu, L., Bennamoun, M., An, S., Sohel, F. & Boussaid, F., 1 Jan 2019, Handbook of Deep Learning Applications. Bales, V. E., Roy, S. S., Sharma, D. & Samui, P. (eds.). USA: Springer Science + Business Media, p. 129-145 17 p. (Smart Innovation, Systems and Technologies; vol. 136).

  Research output: Chapter in Book/Conference paper › Chapter

  • Deep Learning
  • Deep learning
  • Computer Vision
  • Computer vision
  • Plankton
  7 Citations (Scopus)

• Deep learning for scene understanding

  Nadeem, U., Shah, S. A. A., Sohel, F., Togneri, R. & Bennamoun, M., 19 Mar 2019, Handbook of deep learning applications. Balas, V. E., Roy, S. S., Sharma, D. & Samui, P. (eds.). Cham: Springer, p. 21-51 27 p. (Smart Innovation, Systems and Technologies; vol. 136).

  Research output: Chapter in Book/Conference paper › Chapter

  • Deep learning
  • Computer vision
  • Neural networks
  • Network architecture
  • Computer hardware
  2 Citations (Scopus)

• Deep neural networks for mobile person recognition with audio-visual signals

  Alam, M., Bennamoun, M., Togneri, R. & Sohel, F., Sep 2017, Mobile Biometrics. Guo, G. & Wechsler, H. (eds.). London: The Institution of Engineering and Technology, p. 97-129 (IET Book Series on Advances in Biometrics).

  Research output: Chapter in Book/Conference paper › Chapter

  • Deep neural networks
  • Biometrics
  • Cellular telephones
  • Face recognition

• RGB-D Image-Based Object Detection: From Traditional Methods to Deep Learning Techniques

  Ward, I. R., Laga, H. & Bennamoun, M., 27 Oct 2019, RGB-D Image Analysis and Processing. Rosin, P. L., Lai, Y-K., Shao, L. & Liu, Y. (eds.). Netherlands: Springer, p. 169-201 33 p. (Advances in Computer Vision and Pattern Recognition).

  Research output: Chapter in Book/Conference paper › Chapter

  • Object detection
  • Deep learning
  • Computer vision
  • Availability
  • Learning algorithms

• Sparse Representation for View - Based Face Recognition

  Naseem, I., Togneri, R. & Bennamoun, M., 2011, Advances in Face Image Analysis: Techniques and Technologies. Zhang, Y-J. (ed.). United States: IGI Global, p. 164-177

  Research output: Chapter in Book/Conference paper › Chapter
• Conference article

  Attention in Convolutional LSTM for Gesture Recognition

  Shah, S., Bennamoun, M. & Zhang, L., 1 Oct 2018, In : Advances in Neural Information Processing Systems.

  Research output: Contribution to journal › Conference article

  • Long short-term memory
  • Gesture recognition
  • Fusion reactions
  • Convolution
  • Neural networks
  13 Citations (Scopus)

• Improving semantic image segmentation with a probabilistic superpixel-based fully connected CRF

  Zhang, L., Li, H., Zhu, G., Shen, P., Shah, S. A. & Bennamoun, M., 12 Mar 2018, In : IEEE Access. 6, p. 15297 - 15310

  Research output: Contribution to journal › Conference article

  • Superpixels
  • Image segmentation
  • Semantics
  • Pixels
  • Neural networks
• Conference paper

  2D and 3D face recognition using convolutional neural network

  Hu, H., Shah, S. A. A., Bennamoun, M. & Molton, M., 19 Dec 2017, TENCON 2017 - 2017 IEEE Region 10 Conference. USA: IEEE, Institute of Electrical and Electronics Engineers, Vol. 2017-December. p. 133-138 6 p.

  Research output: Chapter in Book/Conference paper › Conference paper

  • Face recognition
  • Neural networks
  • Chemical activation
  • Lighting
  • Testing
  10 Citations (Scopus)

• A 3D Audio-visual Corpus for Speech Recognition

  Sui, C., Haque, S., Togneri, R. & Bennamoun, M., 2012, Proceedings of the 14th Australasian International Conference on Speech Science and Technology. Australia: Australasian Speech Science and Technology Association Inc, Vol. 14. p. 125-128

  Research output: Chapter in Book/Conference paper › Conference paper

• A deep neural network for audio-visual person recognition

  Alam, M. R., Bennamoun, M., Togneri, R. & Sohel, F., 2015, Biometrics Theory, Applications and Systems (BTAS), 2015 IEEE 7th International Conference . USA: IEEE, Institute of Electrical and Electronics Engineers, Vol. N/A. p. 1-6

  Research output: Chapter in Book/Conference paper › Conference paper

  • Deep neural networks
  • Bayesian networks
  • Linear regression
  • Biometrics
  • Support vector machines
  6 Citations (Scopus)

• A Fully Automatic Framework for Prediction of 3D Facial Rejuvenation

  Shah, S. & Bennamoun, M., 4 Feb 2019, 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE, Institute of Electrical and Electronics Engineers, 6 p. 8634657

  Research output: Chapter in Book/Conference paper › Conference paper

  • Cosmetics
  • Fillers
  • Machine learning

• A Model-based Approach to Speaker Identification using Class-specific Dictionaries

  Naseem, I., Togneri, R. & Bennamoun, M., 2012, Proceedings of the 14th Australasian International Conference on Speech Science and Technology. Australia: Australasian Speech Science and Technology Association Inc, Vol. 14. p. 57-60

  Research output: Chapter in Book/Conference paper › Conference paper

• A new representation of skeleton sequences for 3D action recognition

  Ke, Q., Bennamoun, M., An, S., Sohel, F. & Boussaid, F., 2017, Proceedings: 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. United States: IEEE, Institute of Electrical and Electronics Engineers, p. 4570-4579

  Research output: Chapter in Book/Conference paper › Conference paper

  Open Access

  • Trajectories
  • Neural networks
  238 Citations (Scopus)

• An HMM-SVM-Based Automatic Image Annotation Approach

  Lei, Y., Wong, W., Liu, W. & Bennamoun, M., 2011, Computer Vision - ACCV 2010. Germany: Springer, Vol. 6495. p. 115-126

  Research output: Chapter in Book/Conference paper › Conference paper
  5 Citations (Scopus)

• An Improved Approach to Weakly Supervised Semantic Segmentation

  Xu, L., Bennamoun, M., An, S., Boussaid, F. & Sohel, F., 2019, International Conference on Acoustics, Speech, and Signal Processing (ICASSP). USA: IEEE, Institute of Electrical and Electronics Engineers, p. 1897-1901 8682788

  Research output: Chapter in Book/Conference paper › Conference paper

  • Semantics
  • Volatile organic compounds
  • Deep neural networks
  • Image segmentation
  • Labels
  2 Citations (Scopus)

• A novel algorithm for efficient depth segmentation using low resolution (Kinect) images

  Shah, S. A., Bennamoun, M. & Boussaid, F., 2015, IEEE Conference on Industrial Electronics and Applications. Online: IEEE, Institute of Electrical and Electronics Engineers, Vol. N/A. p. 603-607

  Research output: Chapter in Book/Conference paper › Conference paper
  8 Citations (Scopus)

• A Novel Approach to Calculate Body Segments Inertial Parameters from DXA and 3D Scanners Data

  Mourao Rossi, M., El-Sallam Abd, A., Benjanuvatra, N., Lyttle, A., Blanksby, B. & Bennamoun, M., 2012, Proceedings of the 4th International Conference on Computational Methods (ICCM2012). Australia: ICCM, Vol. 1. p. 1-9

  Research output: Chapter in Book/Conference paper › Conference paper

• A robust variable step size fractional least mean square (RVSS-FLMS) algorithm

  Khan, S., Usman, M., Naseem, I., Togneri, R. & Bennamoun, M., 2017, Proceedings - 2017 IEEE 13th International Colloquium on Signal Processing and its Applications, CSPA 2017. Taib, M. N. (ed.). IEEE, Institute of Electrical and Electronics Engineers, p. 1-6 6 p. 8064914

  Research output: Chapter in Book/Conference paper › Conference paper

  • Identification (control systems)
  • system identification
  • Experiments
  • evaluation
  7 Citations (Scopus)

• A structured template based 3D face recognition approach

  Lei, Y., Bennamoun, M. & El-Sallam Abd, A., 2012, Proceedings of the 27th Conference on Image and Vision Computing New Zealand. USA: Association for Computing Machinery (ACM), Vol. 1. p. 61-66

  Research output: Chapter in Book/Conference paper › Conference paper
  1 Citation (Scopus)

• A Training-Free Mesh Upsampling and Morphing Technique for 3D Face Rejuvenation

  Shah, S., Bennamoun, M. & Molton, M., 7 Feb 2019, 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE, Institute of Electrical and Electronics Engineers, 8634685. (International Conference Image and Vision Computing New Zealand; vol. 2018-November).

  Research output: Chapter in Book/Conference paper › Conference paper

  • Pixels

• Automatic 3D Face Landmark Localization Based on 3D Vector Field Analysis

  Shah, S. A. A., Bennamoun, M. & Boussaid, F., 2015, 2015 International Conference on Image and Vision Computing New Zealand (IVCNZ). Auckland, NZ: Wiley-IEEE Press

  Research output: Chapter in Book/Conference paper › Conference paper

  • Animation
  • Face recognition
  1 Citation (Scopus)

• Bi-SAN-CAP: Bi-Directional Self-Attention for Image Captioning

  Hossain, M. Z., Sohel, F., Shiratuddin, M. F., Laga, H. & Bennamoun, M., 1 Dec 2019, 2019 Digital Image Computing: Techniques and Applications, DICTA 2019. IEEE, Institute of Electrical and Electronics Engineers, 8946003. (2019 Digital Image Computing: Techniques and Applications, DICTA 2019).

  Research output: Chapter in Book/Conference paper › Conference paper

  • Long short-term memory
  • Pipelines
  • Neural networks
  1 Citation (Scopus)