Find Research outputs

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• Article

  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)

• Orthogonal Deep Models as Defense against Black-Box Attacks

  Jalwana, M. A. A. K., Akhtar, N., Bennamoun, M. & Mian, A., 2020, In : IEEE Access. 8, p. 119744-119757 14 p., 9129688.

  Research output: Contribution to journal › Article

  Open Access

  • Deep learning
  • Computer vision

• 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)

• Redundancy and Attention in Convolutional LSTM for Gesture Recognition

  Zhu, G., Zhang, L., Yang, L., Mei, L., Shah, S. A. A., Bennamoun, M. & Shen, P., Apr 2020, In : IEEE Transactions on Neural Networks and Learning Systems. 31, 4, p. 1323-1335 13 p., 8750878.

  Research output: Contribution to journal › Article

  • Long short-term memory
  • Gesture recognition
  • Redundancy
  • Convolution
  • Fusion reactions
  3 Citations (Scopus)

• ResFeats: Residual network based features for underwater image classification

  Mahmood, A., Bennamoun, M., An, S., Sohel, F. & Boussaid, F., Jan 2020, In : Image and Vision Computing. 93, 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)

• 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-Aware Feature Network for Weakly Supervised Semantic Segmentation

  Xu, L., Bennamoun, M., Boussaid, F. & Sohel, F., 21 Apr 2020, In : IEEE Access. 8, p. 75957-75967 11 p., 9075085.

  Research output: Contribution to journal › Article

  Open Access

  • Semantics
  • Volatile organic compounds
  • Image classification
  • Convolution
  • Image segmentation

• 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)

• Similarity Based Block Sparse Subset Selection for Video Summarization

  Ma, M., Mei, S., Wan, S., Wang, Z., Feng, D. D. & Bennamoun, M., 14 Dec 2020, In : IEEE Transactions on Circuits and Systems for Video Technology.

  Research output: Contribution to journal › Article

  • Deep learning
  • Set theory
  • Vector spaces

• 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
  10 Citations (Scopus)

• 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)

• Topology-learnable graph convolution for skeleton-based action recognition

  Zhu, G., Zhang, L., Li, H., Shen, P., Shah, S. A. A. & Bennamoun, M., Jul 2020, In : Pattern Recognition Letters. 135, p. 286-292 7 p.

  Research output: Contribution to journal › Article

  • Convolution
  • Topology
  • Fusion reactions
  • Deep learning
  • Set theory
  4 Citations (Scopus)

• Unsupervised segmentation of unknown objects in complex environments

  Asif, U., Bennamoun, M. & Sohel, F., Jun 2016, In : Autonomous Robots. 40, 5, p. 805-829

  Research output: Contribution to journal › Article
  10 Citations (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
  16 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
  3 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
  8 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)

• 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

• Vision to Language: Methods, Metrics and Datasets

  Sharif, N., Nadeem, U., Shah, S. A. A., Bennamoun, M. & Liu, W., 2020, Machine Learning Paradigms: Advances in Deep Learning-based Technological Applications. Tsihrintzis, G. A. & Jain, L. C. (eds.). Cham: Springer International Publishing, p. 9-62 54 p. (Learning and Analytics in Intelligent Systems; vol. 18).

  Research output: Chapter in Book/Conference paper › Chapter

  • Deep learning
  • Artificial intelligence
  • Object recognition
  • Speech recognition
  • Computer vision

• Visual Speech Feature Representations: Recent Advances

  Sui, C., Bennamoun, M. & Togneri, R., 2016, Advances in Face Detection and Facial Image Analysis. Kawulok, M., Celebi, E. & Smolka, B. (eds.). USA: Springer US, p. 377-396 20 p.

  Research output: Chapter in Book/Conference paper › Chapter
  2 Citations (Scopus)
• Conference article

  Attack to Explain Deep Representation

  Jalwana, M. A. A. K., Akhtar, N., Bennamoun, M. & Mian, A., 2020, In : Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. p. 9540-9549 10 p., 9156888.

  Research output: Contribution to journal › Conference article

  • Labels
  • Classifiers
  • Deep learning
  • Casting
  • Demonstrations
  1 Citation (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
  15 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

  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 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

• 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 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 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

• Audio-Visual Biometric Recognition Via Joint Sparse Representations

  Primorac, R., Togneri, R., Bennamoun, M. & Sohel, F., 2016, Proceedings of the 23rd International Conference on Pattern Recognition (ICPR). Bayro-Corrochano, E. (ed.). USA: IEEE, Institute of Electrical and Electronics Engineers, p. 3026-3030

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

  • Biometrics
  • Identification (control systems)
  • Fusion reactions
  • Pixels
  2 Citations (Scopus)

  12 Downloads (Pure)

• Automatic annotation of coral reefs using deep learning

  Mahmood, A., Bennamoun, M., An, S., Sohel, F., Boussaid, F., Hovey, R., Kendrick, G. & Fisher, R. B., 28 Nov 2016, OCEANS 2016 MTS/IEEE Monterey, OCE 2016. Zande, J. & Kirkwood, B. (eds.). IEEE, Institute of Electrical and Electronics Engineers, 7761105

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

  • coral reefs
  • annotations
  • Reefs
  • ecosystems
  • Aquatic ecosystems
  22 Citations (Scopus)

• Binary Descriptor Based on Heat Diffusion for Non-rigid Shape Analysis

  Wang, X., Sohel, F., Bennamoun, M. & Lei, H., 2016, Pacific-Rim Symposium on Image and Video Technology. Bräunl, T., McCane, B., Rivera, M. & Yu, X. (eds.). USA: Springer, p. 751-761 11 p. (Lecture Notes in Computer Science ; vol. 9431).

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

  • Hamming distance
  • Hot Temperature
  • Experiments
  2 Citations (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)

• 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)

• Coral classification using densenet and cross-modality transfer learning

  Xu, L., Bennamoun, M., Boussaid, F., An, S. & Sohel, F., 2019, International Joint Conference on Neural Networks (IJCNN) . USA: IEEE, Institute of Electrical and Electronics Engineers

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

  • Fluorescence
  • Image classification
  1 Citation (Scopus)

• Coral classification with hybrid feature representations

  Mahmood, A., Bennamoun, M., An, S., Sohel, F., Boussaid, F., Hovey, R., Kendrick, G. & Fisher, R., 2016, 2016 IEEE International Conference on Image Processing . Karam, L. (ed.). USA: Wiley-IEEE Press, p. 519-523 5 p.

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

  • Reefs
  • Textures
  • Pixels
  • Color
  38 Citations (Scopus)

• Deep Boltzmann Machines for i-Vector Based Audio-Visual Person Identification

  Alam, M. R., Bennamoun, M., Togneri, R. & Sohel, F., 2016, Image and Video Technology, PSIVT 2015. Bräunl, T., McCane, B., Rivera, M. & Yu, X. (eds.). USA: Springer-Verlag London Ltd., Vol. 9431. p. 631-641 11 p. (Lecture Notes in Computer Science).

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

  • Backpropagation
  • Classifiers
  • Experiments
  3 Citations (Scopus)

• Deep Fusion Net for Coral Classification in Fluorescence and Reflectance Images

  Nadeem, U., Bennamoun, M., Sohel, F. & Togneri, R., Dec 2019, 2019 Digital Image Computing: Techniques and Applications, DICTA 2019. IEEE, Institute of Electrical and Electronics Engineers, 8945925. (2019 Digital Image Computing: Techniques and Applications, DICTA 2019).

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

  • Fluorescence
  • Fusion reactions
  • Reefs
  • Aquatic ecosystems
  • Lighting
  1 Citation (Scopus)

• Direct Image to Point Cloud Descriptors Matching for 6-DOF Camera Localization in Dense 3D Point Clouds

  Nadeem, U., Jalwana, M. A. A. K., Bennamoun, M., Togneri, R. & Sohel, F., 1 Jan 2019, Neural Information Processing - 26th International Conference, ICONIP 2019, Proceedings. Gedeon, T., Wong, K. W. & Lee, M. (eds.). Australia: Springer, p. 222-234 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11954 LNCS).

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

  • Point Cloud
  • Camera
  • Descriptors
  • Cameras
  • Query

• Discrimination comparison between audio and visual features

  Sui, C., Togneri, R., Haque, S. & Bennamoun, M., 2012, 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR 2012). USA: IEEE, Institute of Electrical and Electronics Engineers, Vol. N/A. p. 1609-1612

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

• Efficient Detection of Pixel-Level Adversarial Attacks

  Shah, S. A. A., Bougre, M., Akhtar, N., Bennamoun, M. & Zhang, L., Oct 2020, 2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings. United Arab Emirates: IEEE, Institute of Electrical and Electronics Engineers, p. 718-722 5 p. 9191084. (Proceedings - International Conference on Image Processing, ICIP; vol. 2020-October).

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

  • Pixels
  • Robotics
  • Object recognition
  • Deep learning
  • Chemical activation

• Evaluation of Spatiotemporal Detectors and Descriptors for Facial Expression Recognition

  Hayat, M., Bennamoun, M. & El-Sallam Abd, A., 2012, Proceedings of the 5th International Conference on Human System Interaction. Australia: IEEE, Institute of Electrical and Electronics Engineers, Vol. 1. p. 43-47

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