Mohammed Bennamoun

Search results

• Article

  Progressive conditional GAN-based augmentation for 3D object recognition

  Muzahid, A. A. M., Wanggen, W., Sohel, F., Bennamoun, M., Hou, L. & Ullah, H., 14 Oct 2021, In: Neurocomputing. 460, p. 20-30 11 p.

  Research output: Contribution to journal › Article › peer-review

  • Generative Adversarial Networks 100%
  • Learning Strategy 100%
  • Embedding 100%
  • Object Recognition 75%
  • Classification (Machine Learning) 75%
  2 Citations (Web of Science)

• Pseudo-Pair based Self-Similarity Learning for Unsupervised Person Re-identification

  Wu, L., Liu, D., Zhang, W., Chen, D., Ge, Z., Boussaid, F., Bennamoun, M. & Shen, J., 2022, In: IEEE Transactions on Image Processing. 31, p. 4803-4816 14 p.

  Research output: Contribution to journal › Article › peer-review

  • Person Re-Identification 100%
  • Reidentification 66%
  • Annotation 33%
  • Experimental Result 33%
  • Benchmark 33%
  2 Citations (Web of Science)

• 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 › peer-review

  • Filtered Image 100%
  • Linear Interpolation 28%
  • Image Filtering 28%
  • Compute 14%
  • Computational Cost 14%
  5 Citations (Scopus)

• Quantitative performance evaluation of object detectors in hazy environments

  Hodges, C., Bennamoun, M. & Boussaid, F., Dec 2021, In: Pattern Recognition Letters. 152, p. 150-157 8 p.

  Research output: Contribution to journal › Article › peer-review

  • Neural Networks 100%
  • Quantitative 100%
  • Neural Network 100%
  • Real World 50%
  • Performance Evaluation 50%

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

  Khan, S., Naseem, I., Togneri, R. & Bennamoun, M., 1 Jan 2018, In: IEEE/ACM Transactions on Computational Biology and Bioinformatics. 15, 1, p. 244-250 7 p., 7590067.

  Research output: Contribution to journal › Article › peer-review

  • Classification 100%
  • Manifold 100%
  • Data Set 100%
  • Test Data 100%
  • Learning Task 100%
  24 Citations (Scopus)

• Real time surveillance for low resolution and limited data scenarios: An image set classification approach

  Nadeem, U., Shah, S. A. A., Bennamoun, M., Togneri, R. & Sohel, F., Nov 2021, In: Information Sciences. 580, p. 578-597 20 p.

  Research output: Contribution to journal › Article › peer-review

  • Subspace 100%
  • Test Image 100%
  • Lowest Resolution 66%
  • Test Data 33%
  • Limited Amount 33%
  1 Citation (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 › peer-review

  • Long Short-Term Memory 100%
  • Short-Term Memory 100%
  • Long Short-Term Memory Network 85%
  • Attention Mechanism 71%
  • Gesture Recognition 42%
  31 Citations (Web of Science)

• Reliability Analysis of the Rank Transform for Stereo Matching

  Banks, J. & Bennamoun, M., 2001, In: IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics. 31, 6, p. 870-880

  Research output: Contribution to journal › Article › peer-review

  • Algorithms 100%
  • Matching Algorithm 100%
  • Experimental Result 100%
  • Stereo Matching 100%
  • Stereo Matching Problem 100%
  39 Citations (Scopus)

• Representation and Recognition of 3D Free-Form Objects

  Mamic, G. & Bennamoun, M., 2002, In: Digital Signal Processing. 12, 1, p. 47-76

  Research output: Contribution to journal › Article › peer-review

  • Object Recognition 100%
  • Critical Review 100%
  • Computer Vision 100%
  • Recognition System 33%
  • Object Representation 33%
  45 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 › peer-review

  • Image Classification 100%
  • Experimental Result 25%
  • Imaging Systems 25%
  • Learning Community 25%
  • Extracted Feature 25%
  19 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 › peer-review

  Open Access

  • Case Study 100%
  • Modeling and Simulation 100%
  • Simulation Study 100%
  • Crowd Analysis 100%
  • Information Technology 100%
  13 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 18 p., 7820198.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Object Recognition 100%
  • RGB-D Image 100%
  • Objective Function 50%
  • Point Cloud 50%
  • Uncertainty 25%
  102 Citations (Scopus)

  1165 Downloads (Pure)

• Rigid medical image registration and its association with mutual information

  Fookes, C. & Bennamoun, M., 2003, In: International Journal of Pattern Recognition and Artificial Intelligence. 17, 7, p. 1167-1206

  Research output: Contribution to journal › Article › peer-review

  • Mutual Information 100%
  • Computer Vision 100%
  • Information Measure 25%
  • Entropy 25%
  • Medical Imaging 25%
  5 Citations (Scopus)

• Robust monocular 3D face reconstruction under challenging viewing conditions

  Mohaghegh, H., Boussaid, F., Laga, H., Rahmani, H. & Bennamoun, M., 1 Feb 2023, In: Neurocomputing. 520, p. 82-93 12 p.

  Research output: Contribution to journal › Article › peer-review

  • Viewing Condition 100%
  • Simulation Mode 75%
  • Annotation 50%
  • Invariants 25%
  • Training Data 25%

• Robust real-world point cloud registration by inlier detection

  Huang, X., Wang, Y., Li, S., Mei, G., Xu, Z., Wang, Y., Zhang, J. & Bennamoun, M., Nov 2022, In: Computer Vision and Image Understanding. 224, 103556.

  Research output: Contribution to journal › Article › peer-review

  • Point Cloud 100%
  • Real World 80%
  • Outlier 80%
  • Inlier 80%
  • Registration 40%
  2 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 › peer-review

  • Classification Algorithm 100%
  • Linear Regression 100%
  • Pixel 66%
  • Illumination Variation 33%
  • Benchmark 33%
  113 Citations (Scopus)

• Rotational Projection Statistics for 3D Local Surface Description and Object Recognition

  Guo, Y., Sohel, F., Bennamoun, M., Lu, M. & Wan, J., 2013, In: International Journal of Computer Vision. 105, 1, p. 63-86

  Research output: Contribution to journal › Article › peer-review
  458 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 › peer-review

  Open Access

  • Localisation 100%
  • Scale Feature 66%
  • Multiscale 66%
  • Segmentation 66%
  • Segmentation Model 66%
  2 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 › peer-review

  • Salient Region 100%
  • Challenging Task 25%
  • Experimental Result 25%
  • Segmentation 25%
  • Superior Performance 25%
  24 Citations (Scopus)

• SC-CAN: Spectral Convolution and Channel Attention Network for Wheat Stress Classification

  Khotimah, W. N., Boussaid, F., Sohel, F., Xu, L., Edwards, D., Jin, X. & Bennamoun, M., Sep 2022, In: Remote Sensing. 14, 17, 18 p., 4288.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Attention Network 100%
  • Dataset 80%
  • Convolutional Layer 40%
  • Experimental Result 20%
  • Classification 20%

• ScoreGAN: A Fraud Review Detector BASED on Regulated GAN with Data Augmentation

  Shehnepoor, S., Togneri, R., Liu, W. & Bennamoun, M., 2022, In: IEEE Transactions on Information Forensics and Security. 17, p. 280-291 12 p.

  Research output: Contribution to journal › Article › peer-review

  • Generative Adversarial Networks 100%
  • Neural Network 100%
  • Maximization 100%
  • Generalization 50%
  • Current Solution 25%
  1 Citation (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 › peer-review

  • Conditional Random Field 100%
  • Intersections 60%
  • Inference Algorithm 60%
  • Segmentation 60%
  • Optimization 40%
  18 Citations (Scopus)

• Similarity Based Block Sparse Subset Selection for Video Summarization

  Ma, M., Mei, S., Wan, S., Wang, Z., Feng, D. D. & Bennamoun, M., 1 Oct 2021, In: IEEE Transactions on Circuits and Systems for Video Technology. 31, 10, p. 3967-3980 14 p.

  Research output: Contribution to journal › Article › peer-review

  • Subset Selection 100%
  • Algorithms 100%
  • Video Summarization 85%
  • Optimization Model 50%
  • Optimization 14%
  7 Citations (Scopus)

• Simultaneous Registration of Multiple Corresponding Point Sets

  Williams, J. & Bennamoun, M., 2001, In: Computer Vision and Image Understanding. 81, p. 117-142

  Research output: Contribution to journal › Article › peer-review

  • Set Point 100%
  • Algorithm 66%
  • Compute 33%
  • Real Data 33%
  • Multiple View 33%
  87 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 › peer-review

  • Existing Method 100%
  • Superior Performance 100%
  • Existing Technique 100%
  • Environmental Condition 100%
  • Interference 100%
  27 Citations (Scopus)

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

  Ke, Q., An, S., Bennamoun, M., Sohel, F. & Boussaid, F., Jun 2017, In: IEEE Signal Processing Letters. 24, 6, p. 731-735 5 p., 7891014.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Action Recognition 100%
  • Dataset 75%
  • Temporal Information 50%
  • Invariants 25%
  • Learning Framework 25%
  124 Citations (Scopus)

  706 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 › peer-review

  7 Citations (Scopus)

• Soft Exemplar Highlighting for Cross-View Image-Based Geo-Localization

  Guo, Y., Choi, M., Li, K., Boussaid, F. & Bennamoun, M., 2022, In: IEEE Transactions on Image Processing. 31, p. 2094-2105 12 p.

  Research output: Contribution to journal › Article › peer-review

  • Localisation 100%
  • Aerial Image 50%
  • Experimental Result 25%
  • Benchmark 25%
  • Dataset 25%
  2 Citations (Web of Science)

• 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 › peer-review

  • Optimization 100%
  • Illumination Variation 50%
  • Invariants 50%
  • Linear Subspace 50%
  • Regularization 50%
  49 Citations (Scopus)

• Spatio-Temporal Graph Representation Learning for Fraudster Group Detection

  Shehnepoor, S., Togneri, R., Bennamoun, M. & Liu, W., 25 Oct 2022, (E-pub ahead of print) In: IEEE Transactions on Neural Networks and Learning Systems. p. 1-15 15 p.

  Research output: Contribution to journal › Article › peer-review

  • Fraudster 100%
  • Recurrent Neural Network 50%
  • Representation 50%
  • Representation Learning 50%
  • Outlier 33%

• Tensor pooling-driven instance segmentation framework for baggage threat recognition

  Hassan, T., Akçay, S., Bennamoun, M., Khan, S. & Werghi, N., Jan 2022, In: Neural Computing and Applications. 34, 2, p. 1239-1250 12 p.

  Research output: Contribution to journal › Article › peer-review

  • Instance Segmentation 100%
  9 Citations (Web of Science)

• Text to Image Synthesis for Improved Image Captioning

  Hossain, M. Z., Sohel, F., Shiratuddin, M. F., Laga, H. & Bennamoun, M., 26 Apr 2021, In: IEEE Access. 9, p. 64918 - 64928 11 p., 9416431.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Synthetic Image 100%
  • Experimental Result 33%
  • Synthetic Data 33%
  • Computer Vision 33%
  • Training Data 33%
  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 › peer-review

  • Algorithms 100%
  • Database 50%
  • Classification (Machine Learning) 50%
  • Theoretic Framework 50%
  • Wavelet Packets 50%
  2 Citations (Scopus)

• Three-dimensional image registration as a tool for forensic odontology: A preliminary investigation

  Abduo, J. & Bennamoun, M., 2013, In: American Journal of Forensic Medicine and Pathology. 34, 3, p. 260-266

  Research output: Contribution to journal › Article › peer-review
  14 Citations (Scopus)

• Three Dimensional Model-based Object Recognition and Segmentation in Cluttered Scenes

  Mian, A., Bennamoun, M. & Owens, R., Oct 2006, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 28, 10, p. 1584-1601

  Research output: Contribution to journal › Article › peer-review

  • Tensors 100%
  • Algorithm 40%
  • Recognition Rate 40%
  • Similarities 40%
  • Object Recognition 40%
  422 Citations (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 › peer-review

  Open Access

  • Bulk Density 100%
  • Measurement 83%
  • Gravelly Soils 50%
  • Excavation Method 33%
  • Algorithm 16%
  6 Citations (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 › peer-review

  • Action Recognition 100%
  • Learning Processes 100%
  • Neural Network 100%
  • Initialization 66%
  • Topology Graph 66%
  22 Citations (Scopus)

• Tree-Traversing Ant Algorithm for term clustering based on featureless similarities

  Wong, W., Liu, W. & Bennamoun, M., 2007, In: Data Mining and Knowledge Discovery. 15, 3, p. 349-381

  Research output: Contribution to journal › Article › peer-review

  • Ontology 100%
  • Clustering Method 100%
  • Algorithms 100%
  • Conceptualization 100%
  • Conventional Method 50%
  38 Citations (Scopus)

• Trends in computer-aided manufacturing in prosthodontics: A review of the available streams

  Abduo, J., Lyons, K. M. & Bennamoun, M., 2014, In: International Journal of Dentistry. 2014, p. 1-15

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Computer Aided Manufacturing 100%
  • Prosthesis 100%
  • Prosthetic Dentistry 75%
  • Fabrication 66%
  • Conventional Method 33%
  150 Citations (Scopus)

• Two Novel Complete Sets of Similarity Invariants

  Yu, H. & Bennamoun, M., 2005, In: Lecture Notes in Computer Science. 3804, p. 659-665

  Research output: Contribution to journal › Article › peer-review

  • Invariants 100%
  • Descriptors 66%
  • Original Image 66%
  • Mellin Transform 66%
  • Descriptor 66%

• U-net based analysis of MRI for Alzheimer’s disease diagnosis

  Fan, Z., Li, J., Zhang, L., Zhu, G., Li, P., Lu, X., Shen, P., Shah, S. A. A., Bennamoun, M., Hua, T. & Wei, W., Oct 2021, In: Neural Computing and Applications. 33, 20, p. 13587-13599 13 p.

  Research output: Contribution to journal › Article › peer-review

  • Normal Control 100%
  • Alzheimer's Disease 100%
  • Classification Task 66%
  • Effective Treatment 66%
  • Mild Cognitive Impairment 66%
  9 Citations (Scopus)

• Unsupervised anomaly instance segmentation for baggage threat recognition

  Hassan, T., Akçay, S., Bennamoun, M., Khan, S. & Werghi, N., 2021, (E-pub ahead of print) In: Journal of Ambient Intelligence and Humanized Computing.

  Research output: Contribution to journal › Article › peer-review

  • Baggage 100%
  • Anomaly 57%
  • X Ray 42%
  • Instance Segmentation 28%
  • State of the Art 14%
  11 Citations (Scopus)

• Unsupervised segmentation of unknown objects in complex environments

  Asif, U., Bennamoun, M. & Sohel, F., 1 Jun 2016, In: Autonomous Robots. 40, 5, p. 805-829 25 p.

  Research output: Contribution to journal › Article › peer-review

  • Segmentation 100%
  • Algorithm 100%
  • Algorithms 66%
  • Start() 50%
  • Object Boundary 50%
  14 Citations (Scopus)

• Using ensemble methods to improve the robustness of deep learning for image classification in marine environments

  Wyatt, M., Radford, B., Callow, N., Bennamoun, M. & Hickey, S., Jun 2022, In: Methods in Ecology and Evolution. 13, 6, p. 1317-1328 12 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Classification 100%
  • Ensemble Method 66%
  • Image Classification 66%
  • Learning Approach 33%
  • Calibration 33%
• 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 › peer-review

• 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 › peer-review

  • Convolutional Neural Network 100%
  • Computervision 50%
  • Image Classification 33%
  • Neural Network Model 8%
  • Case Study 8%

• 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 › peer-review

  • Neural Networks 100%
  • Neural Network 100%
  • Natural Languages 66%
  • Natural Language 50%
  • Network Technology 33%

• Object Recognition

  Bennamoun, M. & Mamic, G. J., 2002, U.K.: Springer.

  Research output: Book/Report › Book
• Chapter

  3D Face Surface Analysis and Recognition Based on Facial Surface Features

  Al-Osaimi, F. R. M. & Bennamoun, M., 2013, 3D Face Modeling, Analysis and Recognition. Daoudi, M., Srivastava, A. & Veltkamp, R. (eds.). Australia: John Wiley & Sons, Vol. nil. p. 39-76

  Research output: Chapter in Book/Conference paper › Chapter › peer-review
  2 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 19 p.

  Research output: Chapter in Book/Conference paper › Chapter › peer-review

  • Gesture Recognition 100%
  • Human Motions 66%
  • Convolutional Neural Network 66%
  • Human Motion 66%
  • Learning Framework 33%
  42 Citations (Scopus)