Staff profile

Background

• Depth Estimation and 3D Reconstruction
• Domain Adaptation and Data Augmentation
• Image Processing and Computer Vision
• Machine Learning / Deep Learning
• Multi-Task Learning and Neural Architecture Search
• Robotic Navigation and Autonomy
• Scene Understanding and Image Analysis
• Semantic Segmentation and Object Detection
• Text Ranking and Classification
• Topic Modelling and Sentiment Analysis

Chapter in book

• Atapour-Abarghouei, A., & Breckon, T. (2019). Dealing with Missing Depth: Recent Advances in Depth Image Completion and Estimation. In P. L. Rosin, Y. Lai, L. Shao, & Y. Liu (Eds.), RGB-D image analysis and processing (15-50). Springer Verlag. https://doi.org/10.1007/978-3-030-28603-3_2
• Payen de La Garanderie, G., Atapour Abarghouei, A., & Breckon, T. P. (2018). Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery. In V. Ferrari, M. Hebert, C. Sminchisescu, & Y. Weiss (Eds.), Computer Vision – ECCV 2018 : 15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XII (812-830). Springer Verlag. https://doi.org/10.1007/978-3-030-01261-8_48

Conference Paper

• Towers, D., Forshaw, M., Atapour-Abarghouei, A., & McGough, A. S. (in press). Long-term Reproducibility for Neural Architecture Search.
• Abushofa, M., Atapour-Abarghouei, A., Forshaw, M., & McGough, A. S. (in press). FEGR: Feature Enhanced Graph Representation Method for Graph Classification.
• Cengiz, M., Forshaw, M., Atapour-Abarghouei, A., & McGough, A. S. (2023). Predicting the Performance of a Computing System with Deep Networks. In ICPE '23: Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering (91-98). https://doi.org/10.1145/3578244.3583731
• Battle, M. L., Atapour-Abarghouei, A., & McGough, A. S. (2023). Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets. . https://doi.org/10.1109/bigdata55660.2022.10020820
• Gaus, Y., Bhowmik, N., Issac-Medina, B., Atapour-Abarghouei, A., Shum, H., & Breckon, T. (2023). Region-based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). https://doi.org/10.1109/CVPRW59228.2023.00301
• Chen, S., Atapour-Abarghouei, A., Kerby, J., Ho, E. S., Sainsbury, D. C., Butterworth, S., & Shum, H. P. (2022). A Feasibility Study on Image Inpainting for Non-cleft Lip Generation from Patients with Cleft Lip. . https://doi.org/10.1109/bhi56158.2022.9926917
• Bevan, P. J., & Atapour-Abarghouei, A. (2022). Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification. In K. Kamnitsas, L. Koch, M. Islam, Z. Xu, J. Cardoso, Q. Doi, …S. Tsaftaris (Eds.), DART 2022: Domain Adaptation and Representation Transfer (1-11). https://doi.org/10.1007/978-3-031-16852-9_1
• Bevan, P., & Atapour-Abarghouei, A. (2022). Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification. In K. Chaudhuri, S. Jegelka, L. Song, C. Szepesvari, G. Niu, & S. Sabato (Eds.), Proceedings of Machine Learning Research (1874-1892)
• Blackledge, C., & Atapour-Abarghouei, A. (2021). Transforming Fake News: Robust Generalisable News Classification Using Transformers. . https://doi.org/10.1109/bigdata52589.2021.9671970
• Carrell, S., & Atapour-Abarghouei, A. (2021). Identification of Driver Phone Usage Violations via State-of-the-Art Object Detection with Tracking. . https://doi.org/10.1109/bigdata52589.2021.9671378
• Atapour-Abarghouei, A., Bonner, S., & McGough, A. S. (2021). Rank over Class: The Untapped Potential of Ranking in Natural Language Processing. . https://doi.org/10.1109/bigdata52589.2021.9671386
• Poyser, M., Atapour-Abarghouei, A., & Breckon, T. (2021). On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures. . https://doi.org/10.1109/icpr48806.2021.9412455
• Stelling, J., & Atapour-Abarghouei, A. (2021). “Just Drive”: Colour Bias Mitigation for Semantic Segmentation in the Context of Urban Driving. . https://doi.org/10.1109/bigdata52589.2021.9672033
• Akcay, A., Atapour-Abarghouei, A., & Breckon, T. P. (2019). Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection. In Proceedings of the International Joint Conference on Neural Networks. https://doi.org/10.1109/ijcnn.2019.8851808
• Atapour-Abarghouei, A., & Breckon, T. P. (2019). To complete or to estimate, that is the question: A Multi-Task Depth Completion and Monocular Depth Estimation. In Proceedings of 2019 International Conference on 3D Vision (3DV) (183-193). https://doi.org/10.1109/3dv.2019.00029
• Atapour-Abarghouei, A., & Breckon, T. (2019). Monocular Segment-Wise Depth: Monocular Depth Estimation Based on a Semantic Segmentation Prior. In 2019 IEEE International Conference on Image Processing (ICIP) ; proceedings (4295-4299). https://doi.org/10.1109/icip.2019.8803551
• Aznan, N., Atapour-Abarghouei, A., Bonner, S., Connolly, J., Al Moubayed, N., & Breckon, T. (2019). Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification. In 2019 International Joint Conference on Neural Networks (IJCNN) ; proceedings (1-8). https://doi.org/10.1109/ijcnn.2019.8852227
• Atapour-Abarghouei, A., & Breckon, T. (2019). Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach. In IEEE Conference on Computer Vision and Pattern Recognition, Deep Vision Long Beach, CA, USA, 16-20 June 2019
• Atapour-Abarghouei, A., Bonner, S., & McGough, A. S. (2019). Volenti non fit injuria: Ransomware and its Victims. . https://doi.org/10.1109/bigdata47090.2019.9006298
• Atapour-Abarghouei, A., Bonner, S., & McGough, A. S. (2019). A King’s Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation. In Proceedings of 2019 IEEE International Conference on Big Data (Big Data). https://doi.org/10.1109/bigdata47090.2019.9005540
• Akcay, S., Atapour-Abarghouei, A., & Breckon, T. P. (2019). GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training. In C. Jawahar, H. Li, G. Mori, & K. Schindler (Eds.), Computer Vision – ACCV 2018 : 14th Asian Conference on Computer Vision, Perth, Australia, December 2–6, 2018, Revised Selected Papers, Part III (622-637). https://doi.org/10.1007/978-3-030-20893-6_39
• Bonner, S., Atapour-Abarghouei, A., Jackson, P., Brennan, J., Kureshi, I., Theodoropoulos, G., …Obara, B. (2019). Temporal neighbourhood aggregation: predicting future links in temporal graphs via recurrent variational graph convolutions. In 2019 IEEE International Conference on Big Data (Big Data) (5336-5345). https://doi.org/10.1109/bigdata47090.2019.9005545
• Jackson, P., Atapour-Abarghouei, A., Bonner, S., Breckon, T., & Obara, B. (2019). Style Augmentation: Data Augmentation via Style Randomization.
• Atapour-Abarghouei, A., & Breckon, T. P. (2018). Extended Patch Prioritization for Depth Filling Within Constrained Exemplar-Based RGB-D Image Completion. In A. Campilho, F. Karray, & B. T. H. Romeny (Eds.), Image analysis and recognition : 15th International Conference, ICIAR 2018, Póvoa de Varzim, Portugal, June 27–29, 2018 ; proceedings (306-314). https://doi.org/10.1007/978-3-319-93000-8_35
• Atapour-Abarghouei, A., & Breckon, T. (2018). Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer. In Proc. Computer Vision and Pattern Recognition (2800-2810). https://doi.org/10.1109/CVPR.2018.00296
• Atapour-Abarghouei, A., & Breckon, T. (2017). DepthComp: Real-time Depth Image Completion Based on Prior Semantic Scene Segmentation. In Proc. British Machine Vision Conference (208.1-208.13). https://doi.org/10.5244/C.31.58
• Atapour-Abarghouei, A., de La Garanderie, G. P., & Breckon, T. P. (2016). Back to Butterworth - a Fourier Basis for 3D Surface Relief Hole Filling within RGB-D Imagery. In Proc. Int. Conf. on Pattern Recognition (2813-2818). https://doi.org/10.1109/ICPR.2016.7900062
• Erfani, M., Ghanizadeh, A., Atapour-Abarghouei, A., Sinaie, S., & Shamsuddin, S. M. (2010). A Modified PSO Method Enhanced with Fuzzy Inference System for Solving the Planar Graph Coloring Problem.
• Ghanizadeh, A., Sinaie, S., Atapour-Abarghouei, A., Mozafari, E., & Shamsuddin, S. M. (2010). A Robust Fuzzy and Cellular Learning Automata Edge Detection and Enhancement Method.
• Atapour-Abarghouei, A., Ghanizadeh, A., Sinaie, S., & Shamsuddin, S. M. (2009). A Survey of Pattern Recognition Applications in Cancer Diagnosis. . https://doi.org/10.1109/socpar.2009.93

Doctoral Thesis

• Atapour-Abarghouei, A. (2019). Immaculate Depth Perception: Recovering 3D Scene Information via Depth Completion and Prediction. (Thesis). Durham University. Retrieved from https://durham-repository.worktribe.com/output/1641989

Journal Article

• Chen, S., Atapour-Abarghouei, A., & Shum, H. P. H. (2024). HINT: High-quality INpainting Transformer with Mask-Aware Encoding and Enhanced Attention. IEEE Transactions on Multimedia, https://doi.org/10.1109/TMM.2024.3369897
• Chen, S., Atapour-Abarghouei, A., Ho, E. S., & Shum, H. P. (2023). INCLG: Inpainting for Non-Cleft Lip Generation with a Multi-Task Image Processing Network. Software impacts, 17, Article 100517. https://doi.org/10.1016/j.simpa.2023.100517
• Vali, M., Mohammadi, M., Zarei, N., Samadi, M., Atapour-Abarghouei, A., Supakontanasan, W., …Fard, M. A. (2023). Differentiating Glaucomatous Optic Neuropathy from Non-Glaucomatous Optic Neuropathies Using Deep Learning Algorithms. American Journal of Ophthalmology, 252, 1-8. https://doi.org/10.1016/j.ajo.2023.02.016
• Maciel-Pearson, B., Akcay, S., Atapour-Abarghouei, A., Holder, C., & Breckon, T. (2019). Multi-Task Regression-based Learning for Autonomous Unmanned Aerial Vehicle Flight Control within Unstructured Outdoor Environments. IEEE Robotics and Automation Letters, 4(4), 4116-4123. https://doi.org/10.1109/lra.2019.2930496
• Atapour-Abarghouei, A., Akcay, S., de La Garanderie, G. P., & Breckon, T. P. (2019). Generative Adversarial Framework for Depth Filling via Wasserstein Metric, Cosine Transform and Domain Transfer. Pattern Recognition, 91, 232-244. https://doi.org/10.1016/j.patcog.2019.02.010
• Atapour-Abarghouei, A., & Breckon, T. (2018). A Comparative Review of Plausible Hole Filling Strategies in the Context of Scene Depth Image Completion. Computers and Graphics, 72, 39-58. https://doi.org/10.1016/j.cag.2018.02.001
• Ghanizadeh, A., Atapour-Abarghouei, A., Sinaie, S., Saad, P., & Shamsuddin, S. M. (2011). Iris Segmentation using an Edge Detector based on Fuzzy Sets Theory and Cellular Learning Automata. Applied Optics, 50(19), 3191-3200. https://doi.org/10.1364/ao.50.003191
• Atapour-Abarghouei, A., Ghanizadeh, A., & Shamsuddin, S. M. (2009). Advances of Soft Computing Methods in Edge Detection. International journal of advances in soft computing and its applications, 1(2), 162-203

Masters Thesis

• Atapour-Abarghouei, A. (2010). A Novel Solution to Travelling Salesman Problem using Fuzzy Sets, Gravitational Search Algorithm, and Genetic Algorithm. (Dissertation). [Awarding Organisation: Unknown]. Retrieved from https://durham-repository.worktribe.com/output/1680772