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• 2018

  A Fractional Gradient Descent-Based RBF Neural Network

  Khan, S., Naseem, I., Malik, M. A., Togneri, R. & Bennamoun, M., Dec 2018, In : Circuits, Systems and Signal Processing. 37, 12, p. 5311-5332 22 p.

  Research output: Contribution to journal › Article

  • RBF Neural Network
  • Radial Basis Function Neural Network
  • Gradient Descent
  • Fractional
  • Neural networks
  17 Citations (Scopus)

• 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

• A Multi-modal, Discriminative and Spatially Invariant CNN for RGB-D Object Labeling

  Asif, U., Bennamoun, M. & Sohel, F., 1 Sep 2018, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 40, 9, p. 2051-2065

  Research output: Contribution to journal › Article

  • Labeling
  • Object
  • Neural networks
  • Invariant
  • Image classification
  17 Citations (Scopus)

• An Improved Colour-to-Grey Method Using Image Segmentation and the Colour Difference Model for Colour Vision Deficiency

  Zhang, L., Xu, Q., Zhu, G., Song, J., Zhang, X., Shen, P., Wei, W., Shah, S. A. & Bennamoun, M., 1 Mar 2018, In : IET Image Processing. 12, 3, p. 314 – 319 6 p.

  Research output: Contribution to journal › Article

  • Color vision
  • Image segmentation
  • Color
  10 Citations (Scopus)

• Application of Artificial Intelligence in Coronary Computed Tomography Angiography

  Selvarajah, A., Bennamoun, M., Playford, D., Chow, B. J. W. & Dwivedi, G., 1 Jun 2018, In : Current Cardiovascular Imaging Reports. 11, 6, 12.

  Research output: Contribution to journal › Review article

  • Artificial Intelligence
  • Computed Tomography Angiography
  • Myocardial Fractional Flow Reserve
  • Deep Learning
  • Automation
  3 Citations (Scopus)

• 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
  12 Citations (Scopus)

• Classification of corals in reflectance and fluorescence images using convolutional neural network representations

  Xu, L., Bennamoun, M., An, S., Sohe, F. & Boussaid, F., 10 Sep 2018, 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. IEEE, Institute of Electrical and Electronics Engineers, Vol. 2018-April. p. 1493-1497 5 p. 8462574

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

  • Fluorescence
  • Neural networks
  • Principal component analysis
  • Chemical activation
  5 Citations (Scopus)

• 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 Image Representations for Coral Image Classification

  Mahmood, A., Bennamoun, M., An, S., Sohel, F. A., Boussaid, F., Hovey, R., Kendrick, G. A. & Fisher, R. B., 12 Jan 2018, In : IEEE Journal of Oceanic Engineering. 11 p.

  Research output: Contribution to journal › Article

  Open Access

  File

  • Reefs
  • Image classification
  • Autonomous underwater vehicles
  • Deep learning
  • Aquatic ecosystems
  16 Citations (Scopus)

  444 Downloads (Pure)

• Developing and testing a new machine learning method to identify patients with heart failure who are at risk of 30-day readmission or mortality

  Awan, S. E., Bennamoun, M., Sanfilippo, F., Sohel, F., Shah, S., Rankin, J. & Dwivedi, G., 2018, In : Heart, Lung and Circulation.

  Research output: Contribution to journal › Abstract/Meeting Abstract

• Efficient finer-grained incremental processing with MapReduce for big data

  Zhang, L., Feng, Y., Shen, P., Zhu, G., Wei, W., Song, J., Ali Shah, S. A. & Bennamoun, M., 1 Mar 2018, In : Future Generation Computer Systems. 80, p. 102-111 10 p.

  Research output: Contribution to journal › Article

  • Distributed computer systems
  • Big data
  • Cluster computing
  • Information technology
  • Wear of materials
  3 Citations (Scopus)

• Evolutionary Feature Learning for 3D Object Recognition

  Shah, S. A. A., Bennamoun, M., Boussaid, F. & While, L., 2018, In : IEEE Access. 6, p. 2434-2444

  Research output: Contribution to journal › Article

  Open Access

  • Object recognition
  • Salix
  • Glossaries
  • Navigation
  • Robots
  7 Citations (Scopus)

• Exploiting layerwise convexity of rectifier networks with sign constrained weights

  An, S., Boussaid, F., Bennamoun, M. & Sohel, F., 1 Sep 2018, In : Neural Networks. 105, p. 419-430 12 p.

  Research output: Contribution to journal › Article

  Open Access

  • Weights and Measures
  • Discriminant Analysis
  • Statistical Factor Analysis

• Generating bags of words from the sums of their word embeddings

  White, L., Togneri, R., Liu, W. & Bennamoun, M., 1 Jan 2018, Computational Linguistics and Intelligent Text Processing - 17th International Conference, CICLing 2016, Revised Selected Papers. Gelbukh, A. (ed.). Austria: Springer-Verlag Wien, p. 91-102 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9623 LNCS).

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

  • Information retrieval
  • Semantics
  • Data storage equipment
  • Neural networks
  • Meaning

• Identity Adaptation for Person Re-identification

  Ke, Q., Bennamoun, M., Rahmani, H., An, S., Sohel, F. & Boussaid, F., 30 Aug 2018, In : IEEE Access. 6, p. 48147-48155 8452946.

  Research output: Contribution to journal › Article

  Open Access

  • Testing
  • Deep learning
  • Probability distributions
  • Entropy
  • Cameras
  2 Citations (Scopus)

• Improving Semantic Image Segmentation with a Probabilistic Superpixel-Based Dense Conditional Random Field

  Zhang, L., Li, H., Shen, P., Zhu, G., Song, J., Shah, S. A. A., Zhang, L. & Bennamoun, M., 9 Mar 2018, In : IEEE Access. 6, p. 15297-15310 14 p., 2169-3536.

  Research output: Contribution to journal › Article

  Open Access

  • Superpixels
  • Image segmentation
  • Semantics
  • Neural networks
  • Labels
  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

• Learning-based Composite Metrics for Improved Caption Evaluation

  Sharif, N., Bennamoun, M., White, L. R. & Shah, S., 2018, Proceedings of ACL 2018, Student Research Workshop. Australia: Association for Computational Linguistics, p. 14-20

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

  • Linguistics
  • Composite materials
  • Semantics
  • Image quality
  5 Citations (Scopus)

• Learning Clip Representations for Skeleton-based 3D Action Recognition

  Ke, Q., Bennamoun, M., An, S., Sohel, F. & Boussaid, F., Jun 2018, In : IEEE Transactions on Image Processing. 27, 6, p. 2842-2855

  Research output: Contribution to journal › Article

  • Neural networks
  • Recurrent neural networks
  46 Citations (Scopus)

• Machine learning in heart failure: Ready for prime time

  Awan, S. E., Sohel, F., Sanfilippo, F. M., Bennamoun, M. & Dwivedi, G., 1 Mar 2018, In : Current Opinion in Cardiology. 33, 2, p. 190-195 6 p.

  Research output: Contribution to journal › Review article

  • Machine Learning
  • Deep Learning
  • Heart Failure
  • Big Data
  • Cost Savings
  17 Citations (Scopus)

• 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

• NNEval: Neural Network based Evaluation Metric for Image Captioning

  Sharif, N., White, L. R., Bennamoun, M. & Shah, S., 2018, ECCV. Springer, p. 39-55

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

  Open Access

  • Semantics
  • Neural networks
  • Linguistics
  • Experiments

• NovelPerspective: Identifying Point of View Characters

  White, L., Togneri, R., Liu, W. & Bennamoun, M., 2018, Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics-System Demonstrations. Melbourne: Association for Computational Linguistics, Vol. 2. p. 7-12 6 p.

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

• 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
  9 Citations (Scopus)

• Reflective Field for Pixel-Level Tasks

  Zhang, L., Kong, X., Shen, P., Zhu, G., Shah, S., Bennamoun, M. & Song, J., 10 Oct 2018, Reflective Field for Pixel-Level Tasks. IEEE, Institute of Electrical and Electronics Engineers, p. 529-534

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

  • Pixels
  • Volatile organic compounds
  • Semantics
  • Neural networks

• Resfeats: Residual network based features for image classification

  Mahmood, A., Bennamoun, M., An, S. & Sohel, F., 20 Feb 2018, 2017 IEEE International Conference on Image Processing (ICIP). China: Wiley-IEEE Press, p. 1597-1601

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

• Response to "Ghost Numbers"

  Hayat, M., Bennamoun, M. & An, S., 1 Oct 2018, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 40, 10, 1 p., 8454023.

  Research output: Contribution to journal › Review article

• 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)

• 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
• 2017

  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
  8 Citations (Scopus)

• A Cascade Gray-Stereo Visual Feature Extraction Method For Visual and Audio-Visual Speech Recognition

  Sui, C., Togneri, R. & Bennamoun, M., Jun 2017, In : Speech Communication. 90, p. 26-38 13 p.

  Research output: Contribution to journal › Article

  Open Access

  File

  • Audiovisual Speech
  • Feature Extraction
  • Speech Recognition
  • Cascade
  • Vision
  7 Citations (Scopus)

  245 Downloads (Pure)

• 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
  226 Citations (Scopus)

• A Novel Adaptive Kernel for the RBF Neural Networks

  Khan, S., Naseem, I., Togneri, R. & Bennamoun, M., 1 Apr 2017, In : Circuits, Systems, and Signal Processing. 36, 4, p. 1639-1653 15 p.

  Research output: Contribution to journal › Article

  • RBF Neural Network
  • kernel
  • Neural networks
  • Electric fuses
  • Radial Basis Function Neural Network
  22 Citations (Scopus)

• 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)

• Cost-Sensitive Learning of Deep Feature Representations From Imbalanced Data

  Khan, S. H., Hayat, M., Bennamoun, M., Sohel, F. A. & Togneri, R., 17 Aug 2017, In : IEEE Transactions on Neural Networks and Learning Systems. 29, 8, p. 3573-3587

  Research output: Contribution to journal › Article

  • Costs
  • Classifiers
  • Deep neural networks
  • Image classification
  • Object detection
  177 Citations (Scopus)

• Deep feature learning for dummies: A simple auto-encoder training method using Particle Swarm Optimisation

  Sui, C., Bennamoun, M. & Togneri, R., 15 Jul 2017, In : Pattern Recognition Letters. 94, p. 75-80 6 p.

  Research output: Contribution to journal › Article

  • Deep learning
  • Particle swarm optimization (PSO)
  • Feature extraction
  • Speech recognition
  8 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 on underwater marine object detection: a survey

  Moniruzzaman, M., Islam, S. M. S., Bennamoun, M. & Lavery, P., 2017, International conference on advanced concepts for intelligent vision systems (ACIVS). Springer, Vol. 10617 LNCS. p. 150-160 11 p. (Lecture Notes in Computer Science ).

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

  • Object detection
  • Deep learning
  • Deep neural networks
  • Monitoring
  • Ecosystems
  37 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

• Discriminative feature learning and region consistency activation for robust scene labeling

  Li, Y., Sohel, F., Bennamoun, M. & Lei, H., 21 Jun 2017, In : Neurocomputing. 243, p. 174-186 13 p.

  Research output: Contribution to journal › Article

  • Labeling
  • Chemical activation
  • Learning
  • Generalization (Psychology)
  • Labels

• ECMSRC: A sparse learning approach for the prediction of extracellular matrix proteins

  Naseem, I., Khan, S., Togneri, R. & Bennamoun, M., 1 Aug 2017, In : Current Bioinformatics. 12, 4, p. 361-368 8 p.

  Research output: Contribution to journal › Article

  • Extracellular Matrix Proteins
  • Protein
  • Proteins
  • Learning
  • Extracellular Matrix
  18 Citations (Scopus)

• Efficient Image Set Classification Using Linear Regression Based Image Reconstruction

  Shah, S. A. A., Nadeem, U., Bennamoun, M., Sohel, F. & Togneri, R., 22 Aug 2017, Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017. USA: IEEE, Institute of Electrical and Electronics Engineers, Vol. 2017-July. p. 601-610 10 p. 8014822

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

  • Image reconstruction
  • Linear regression
  17 Citations (Scopus)

• Empowering Simple Binary Classifiers for Image Set Based Face Recognition

  Hayat, M., Khan, S. H. & Bennamoun, M., 1 Jul 2017, In : International Journal of Computer Vision. 123, 3, p. 479-498 20 p.

  Research output: Contribution to journal › Article

  • Face recognition
  • Classifiers
  • Object recognition
  • Security systems
  • Cameras
  18 Citations (Scopus)

• FLMF: Fractional Least Mean Fourth Algorithm for Channel Estimation in non-Gaussian Environment

  Khan, S., Ahmed, N., Malik, M. A., Naseem, I., Togneri, R. & Bennamoun, M., 14 Dec 2017, 2017 International Conference on Information and Communication Technology Convergence. USA: Wiley-IEEE Press, p. 466-470 5 p. (International Conference on Information and Communication Technology Convergence).

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

• Forest Change Detection in Incomplete Satellite Images With Deep Neural Networks

  Khan, S. H., He, X., Porikli, F. & Bennamoun, M., Sep 2017, In : IEEE Transactions on Geoscience and Remote Sensing. 55, 9, p. 5407 - 5423

  Research output: Contribution to journal › Article

  • Deep neural networks
  • satellite image
  • Satellites
  • detection
  • Monitoring
  46 Citations (Scopus)

• Keypoints-based surface representation for 3D modeling and 3D object recognition

  Shah, S. A. A., Bennamoun, M. & Boussaid, F., 1 Apr 2017, In : Pattern Recognition. 64, p. 29-38 10 p.

  Research output: Contribution to journal › Article

  • 3D modeling
  • Object recognition
  • Image registration
  • Tensors
  • MATLAB
  35 Citations (Scopus)

• Learning Action Recognition Model from Depth and Skeleton Videos

  Rahmani, H. & Bennamoun, M., 22 Dec 2017, Proceedings of the 2017 IEEE International Conference on Computer Vision, ICCV 2017. IEEE, Institute of Electrical and Electronics Engineers, Vol. 2017-October. p. 5833-5842 10 p. 8237883

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

  • Sensors
  50 Citations (Scopus)

• Learning deep structured network for weakly supervised change detection

  Khan, S. H., He, X., Porikli, F., Bennamoun, M., Sohel, F. & Togneri, R., 25 Aug 2017, 2017 International Joint Conference on Artificial Intelligence. Sierra, C. (ed.). Australia: International Joint Conferences on Artificial Intelligence, p. 2008-2015

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

  15 Citations (Scopus)

• Learning Spatiotemporal Features using 3DCNN and Convolutional LSTM for Gesture Recognition

  Zhang, L., Zhu, G., Shen, P., Song, J., Shah, S. & Bennamoun, M., 1 Aug 2017, Learning Spatiotemporal Features using 3DCNN and Convolutional LSTM for Gesture Recognition. IEEE, Institute of Electrical and Electronics Engineers, p. 3120-3128

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

  • Gesture recognition
  • Neural networks
  • Long short-term memory
  • Experiments
  64 Citations (Scopus)