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

• Dealing with Missing Depth: Recent Advances in Depth Image Completion and Estimation
  Atapour-Abarghouei, A., & Breckon, T. (2019). Dealing with Missing Depth: Recent Advances in Depth Image Completion and Estimation. In P. L. Rosin, Y.-K. 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
• Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery
  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

• Deep Learning-Enhanced Visual Monitoring in Hazardous Underwater Environments with a Swarm of Micro-Robots
  Chen, S., He, Y., Lennox, B., Arvin, F., & Atapour-Abarghouei, A. (2025, May). Deep Learning-Enhanced Visual Monitoring in Hazardous Underwater Environments with a Swarm of Micro-Robots. Presented at IEEE International Conference on Robotics & Automation, Atlanta, USA
• FineCausal: A Causal-Based Framework for Interpretable Fine-Grained Action Quality Assessment
  Han, R., Zhou, K., Atapour-Abarghouei, A., Liang, X., & Shum, H. P. H. (2025, June). FineCausal: A Causal-Based Framework for Interpretable Fine-Grained Action Quality Assessment. Presented at Proceedings of the 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025, Music City Center, Nashville TN
• Dur360BEV: A Real-world 360-degree Single Camera Dataset and Benchmark for Bird-Eye View Mapping in Autonomous Driving
  E, W., Yuan, C., Sun, Y., Gaus, Y., Atapour-Abarghouei, A., & Breckon, T. (2025, May). Dur360BEV: A Real-world 360-degree Single Camera Dataset and Benchmark for Bird-Eye View Mapping in Autonomous Driving. Presented at IEEE International Conference on Robotics and Automation (ICRA), Atlanta, USA
• Long-term Reproducibility for Neural Architecture Search
  Towers, D., Forshaw, M., Atapour-Abarghouei, A., & McGough, A. S. (2022, June). Long-term Reproducibility for Neural Architecture Search. Presented at IEEE/CVF Computer Vision and Pattern Recognition Conference Workshops, New Orleans, USA
• DurTOMD: A Trail-based Off-road Multimodal Dataset for Traversable Pathway Segmentation under Challenging Illumination Conditions
  Sun, Y., Li, L., E, W., Atapour-Abarghouei, A., & Breckon, T. (2025, June). DurTOMD: A Trail-based Off-road Multimodal Dataset for Traversable Pathway Segmentation under Challenging Illumination Conditions. Presented at International Joint Conference on Neural Networks, Rome, Italy
• Beyond Syntax: How Do LLMs Understand Code?
  North, M., Atapour-Abarghouei, A., & Bencomo, N. (2025, April). Beyond Syntax: How Do LLMs Understand Code?. Presented at 2025 IEEE/ACM International Conference on Software Engineering ICSE, Ottawa , Canada
• SEM-Net: Efficient Pixel Modelling for Image Inpainting with Spatially Enhanced SSM
  Chen, S., Zhang, H., Atapour-Abarghouei, A., & Shum, H. P. H. (2025, February). SEM-Net: Efficient Pixel Modelling for Image Inpainting with Spatially Enhanced SSM. Presented at 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Tucson, Arizona
• Insights from the Use of Previously Unseen Neural Architecture Search Datasets
  Geada, R., Towers, D., Forshaw, M., Atapour-Abarghouei, A., & Mcgough, A. S. (2024, June). Insights from the Use of Previously Unseen Neural Architecture Search Datasets. Presented at IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), Seattle, WA
• Code Gradients: Towards Automated Traceability of LLM-Generated Code
  North, M., Atapour-Abarghouei, A., & Bencomo, N. (2024, June). Code Gradients: Towards Automated Traceability of LLM-Generated Code. Presented at 2024 IEEE 32nd International Requirements Engineering Conference (RE), Reykjavik, Iceland
• Disentangling Racial Phenotypes: Fine-Grained Control of Race-related Facial Phenotype Characteristics
  Yucer, S., Abarghouei, A. A., Al Moubayed, N., & Breckon, T. P. (2024, June). Disentangling Racial Phenotypes: Fine-Grained Control of Race-related Facial Phenotype Characteristics. Presented at 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan
• FEGR: Feature Enhanced Graph Representation Method for Graph Classification
  Abushofa, M., Atapour-Abarghouei, A., Forshaw, M., & McGough, A. S. (2023, November). FEGR: Feature Enhanced Graph Representation Method for Graph Classification. Presented at 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Kusadasi, Turkey
• MxT: Mamba x Transformer for Image Inpainting
  Chen, S., Atapour-Abarghouei, A., Zhang, H., & Shum, H. P. H. (2024, November). MxT: Mamba x Transformer for Image Inpainting. Presented at BMVC 2024: The 35th British Machine Vision Conference, Glasgow, UK
• Predicting the Performance of a Computing System with Deep Networks
  Cengiz, M., Forshaw, M., Atapour-Abarghouei, A., & McGough, A. S. (2023, April). Predicting the Performance of a Computing System with Deep Networks. Presented at 2023 ACM/SPEC International Conference on Performance Engineering (ICPE ’23), Coimbra, Portugal
• Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets
  Battle, M. L., Atapour-Abarghouei, A., & McGough, A. S. (2022, December). Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets. Presented at 2022 IEEE International Conference on Big Data, Osaka, Japan
• Region-based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery
  Gaus, Y., Bhowmik, N., Issac-Medina, B., Atapour-Abarghouei, A., Shum, H., & Breckon, T. (2023, June). Region-based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery. Presented at IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023, Vancouver, BC
• Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification
  Bevan, P., & Atapour-Abarghouei, A. (2022, July). Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification. Presented at The 39th International Conference on Machine Learning (ICML 2022), Baltimore, MD
• A Feasibility Study on Image Inpainting for Non-cleft Lip Generation from Patients with Cleft Lip
  Chen, S., Atapour-Abarghouei, A., Kerby, J., Ho, E. S., Sainsbury, D. C., Butterworth, S., & Shum, H. P. (2022, September). A Feasibility Study on Image Inpainting for Non-cleft Lip Generation from Patients with Cleft Lip. Presented at 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), Ioannina, Greece
• Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification
  Bevan, P. J., & Atapour-Abarghouei, A. (2022, December). Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification. Presented at DART: MICCAI Workshop on Domain Adaptation and Representation Transfer
• Transforming Fake News: Robust Generalisable News Classification Using Transformers
  Blackledge, C., & Atapour-Abarghouei, A. (2021, December). Transforming Fake News: Robust Generalisable News Classification Using Transformers. Presented at 2021 IEEE International Conference on Big Data (IEEE BigData 2021), Orlando, FL, USA
• Rank over Class: The Untapped Potential of Ranking in Natural Language Processing
  Atapour-Abarghouei, A., Bonner, S., & McGough, A. S. (2021, December). Rank over Class: The Untapped Potential of Ranking in Natural Language Processing. Presented at 2021 IEEE International Conference on Big Data (IEEE BigData 2021), Orlando, FL, USA
• Identification of Driver Phone Usage Violations via State-of-the-Art Object Detection with Tracking
  Carrell, S., & Atapour-Abarghouei, A. (2021, December). Identification of Driver Phone Usage Violations via State-of-the-Art Object Detection with Tracking. Presented at 2021 IEEE International Conference on Big Data (IEEE BigData 2021), Orlando, FL, USA
• “Just Drive”: Colour Bias Mitigation for Semantic Segmentation in the Context of Urban Driving
  Stelling, J., & Atapour-Abarghouei, A. (2021, December). “Just Drive”: Colour Bias Mitigation for Semantic Segmentation in the Context of Urban Driving. Presented at 2021 IEEE International Conference on Big Data (IEEE BigData 2021), Orlando, FL, USA
• On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures
  Poyser, M., Atapour-Abarghouei, A., & Breckon, T. (2021, January). On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures. Presented at 25th International Conference on Pattern Recognition (ICPR2020), Milan, Italy
• Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection
  Akcay, A., Atapour-Abarghouei, A., & Breckon, T. P. (2019, July). Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection. Presented at Proc. Int. Joint Conference on Neural Networks, Budapest, Hungary
• To complete or to estimate, that is the question: A Multi-Task Depth Completion and Monocular Depth Estimation
  Atapour-Abarghouei, A., & Breckon, T. P. (2019, September). To complete or to estimate, that is the question: A Multi-Task Depth Completion and Monocular Depth Estimation. Presented at International Conference on 3D Vision, Quebec
• Monocular Segment-Wise Depth: Monocular Depth Estimation Based on a Semantic Segmentation Prior
  Atapour-Abarghouei, A., & Breckon, T. (2019, September). Monocular Segment-Wise Depth: Monocular Depth Estimation Based on a Semantic Segmentation Prior. Presented at IEEE International Conference on Image Processing, Taipei, Taiwen
• Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification
  Aznan, N., Atapour-Abarghouei, A., Bonner, S., Connolly, J., Al Moubayed, N., & Breckon, T. (2019, December). Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification. Presented at International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary
• Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach
  Atapour-Abarghouei, A., & Breckon, T. (2019, June). Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach. Presented at IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, California, USA
• GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
  Akcay, S., Atapour-Abarghouei, A., & Breckon, T. P. (2018, December). GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training. Presented at 14th Asian Conference on Computer Vision (ACCV)., Perth, Australia
• Volenti non fit injuria: Ransomware and its Victims
  Atapour-Abarghouei, A., Bonner, S., & McGough, A. S. (2019, December). Volenti non fit injuria: Ransomware and its Victims. Presented at 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA
• A King’s Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation
  Atapour-Abarghouei, A., Bonner, S., & McGough, A. S. (2019, December). A King’s Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation. Presented at 2019 IEEE International Conference on Big Data (Big Data)
• Style Augmentation: Data Augmentation via Style Randomization
  Jackson, P., Atapour-Abarghouei, A., Bonner, S., Breckon, T., & Obara, B. (2019, June). Style Augmentation: Data Augmentation via Style Randomization. Presented at IEEE/CVF Conference on Computer Vision and Pattern Recognition, Deep Vision, Long Beach, CA, USA
• Temporal neighbourhood aggregation: predicting future links in temporal graphs via recurrent variational graph convolutions
  Bonner, S., Atapour-Abarghouei, A., Jackson, P., Brennan, J., Kureshi, I., Theodoropoulos, G., McGough, S., & Obara, B. (2019, December). Temporal neighbourhood aggregation: predicting future links in temporal graphs via recurrent variational graph convolutions. Presented at IEEE International Conference on Big Data (Deep Graph Learning: Methodologies and Applications), Los Angeles, CA, USA
• Extended Patch Prioritization for Depth Filling Within Constrained Exemplar-Based RGB-D Image Completion
  Atapour-Abarghouei, A., & Breckon, T. P. (2018, December). Extended Patch Prioritization for Depth Filling Within Constrained Exemplar-Based RGB-D Image Completion. Presented at International Conference Image Analysis and Recognition, Póvoa de Varzim, Portugal
• Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer
  Atapour-Abarghouei, A., & Breckon, T. (2018, June). Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer. Presented at 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)., Salt Lake City, Utah, USA
• DepthComp: Real-time Depth Image Completion Based on Prior Semantic Scene Segmentation
  Atapour-Abarghouei, A., & Breckon, T. (2017, September). DepthComp: Real-time Depth Image Completion Based on Prior Semantic Scene Segmentation. Presented at 28th British Machine Vision Conference (BMVC) 2017, London, UK
• Back to Butterworth - a Fourier Basis for 3D Surface Relief Hole Filling within RGB-D Imagery
  Atapour-Abarghouei, A., de La Garanderie, G. P., & Breckon, T. P. (2016, December). Back to Butterworth - a Fourier Basis for 3D Surface Relief Hole Filling within RGB-D Imagery. Presented at 2016 23rd International Conference on Pattern Recognition (ICPR), Cancun
• A Modified PSO Method Enhanced with Fuzzy Inference System for Solving the Planar Graph Coloring Problem
  Erfani, M., Ghanizadeh, A., Atapour-Abarghouei, A., Sinaie, S., & Shamsuddin, S. M. (2010, December). A Modified PSO Method Enhanced with Fuzzy Inference System for Solving the Planar Graph Coloring Problem. Presented at International Conference on Artificial Intelligence
• A Robust Fuzzy and Cellular Learning Automata Edge Detection and Enhancement Method
  Ghanizadeh, A., Sinaie, S., Atapour-Abarghouei, A., Mozafari, E., & Shamsuddin, S. M. (2010, December). A Robust Fuzzy and Cellular Learning Automata Edge Detection and Enhancement Method. Presented at International Conference on Image Processing, Computer Vision, & Pattern Recognition, Las Vegas, Nevada
• A Survey of Pattern Recognition Applications in Cancer Diagnosis
  Atapour-Abarghouei, A., Ghanizadeh, A., Sinaie, S., & Shamsuddin, S. M. (2009, December). A Survey of Pattern Recognition Applications in Cancer Diagnosis. Presented at International Conference on Soft Computing and Pattern Recognition, Malacca

Doctoral Thesis

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

Journal Article

• Diagnosis of multiple sclerosis by detecting asymmetry within the retina using a similarity-based neural network
  Bolton, R. C., Kafieh, R., Ashtari, F., & Atapour-Abarghouei, A. (2024). Diagnosis of multiple sclerosis by detecting asymmetry within the retina using a similarity-based neural network. IEEE Access, 12, 62975-62985. https://doi.org/10.1109/access.2024.3395995
• HINT: High-quality INpainting Transformer with Mask-Aware Encoding and Enhanced Attention
  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, 26, 7649-7660. https://doi.org/10.1109/TMM.2024.3369897
• INCLG: Inpainting for Non-Cleft Lip Generation with a Multi-Task Image Processing Network
  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
• Differentiating Glaucomatous Optic Neuropathy from Non-Glaucomatous Optic Neuropathies Using Deep Learning Algorithms
  Vali, M., Mohammadi, M., Zarei, N., Samadi, M., Atapour-Abarghouei, A., Supakontanasan, W., Suwan, Y., Subramanian, P. S., Miller, N. R., Kafieh, R., & 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
• Multi-Task Regression-based Learning for Autonomous Unmanned Aerial Vehicle Flight Control within Unstructured Outdoor Environments
  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
• Generative Adversarial Framework for Depth Filling via Wasserstein Metric, Cosine Transform and Domain Transfer
  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
• A Comparative Review of Plausible Hole Filling Strategies in the Context of Scene Depth Image Completion
  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
• Iris Segmentation using an Edge Detector based on Fuzzy Sets Theory and Cellular Learning Automata
  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
• Advances of Soft Computing Methods in Edge Detection
  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

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