Local representation learning with a convolutional autoencoder
(2018)
Presentation / Conference Contribution
Kenning, M. P., Xie, X., Edwards, M., & Deng, J. (2018). Local representation learning with a convolutional autoencoder. . https://doi.org/10.1109/icip.2018.8451233
Outputs (663)
Protein classification using Hidden Markov models and randomised decision trees (2014)
Presentation / Conference Contribution
Lacey, A., Deng, J., & Xie, X. (2014). Protein classification using Hidden Markov models and randomised decision trees. . https://doi.org/10.1109/bmei.2014.7002856
RHapTor: Rendering Haptic Torques for Virtual Reality (2022)
Presentation / Conference Contribution
Roice, K., & Koulieris, G. A. (2022). RHapTor: Rendering Haptic Torques for Virtual Reality. . https://doi.org/10.1145/3532719.3543248
On Fine-tuned Deep Features for Unsupervised Domain Adaptation (2023)
Presentation / Conference Contribution
Wang, Q., Meng, F., & Breckon, T. (2023). On Fine-tuned Deep Features for Unsupervised Domain Adaptation. . https://doi.org/10.1109/IJCNN54540.2023.10191262Prior feature transformation based approaches to Unsupervised Domain Adaptation (UDA) employ the deep features extracted by pre-trained deep models without fine-tuning them on the specific source or target domain data for a particular domain adaptati... Read More about On Fine-tuned Deep Features for Unsupervised Domain Adaptation.
MedNeRF: Medical Neural Radiance Fields for Reconstructing 3D-aware CT-Projections from a Single X-ray (2022)
Presentation / Conference Contribution
Corona-Figueroa, A., Frawley, J., Bond-Taylor, S., Bethapudi, S., Shum, H. P., & Willcocks, C. G. (2022). MedNeRF: Medical Neural Radiance Fields for Reconstructing 3D-aware CT-Projections from a Single X-ray. . https://doi.org/10.1109/embc48229.2022.9871757Computed tomography (CT) is an effective med-ical imaging modality, widely used in the field of clinical medicine for the diagnosis of various pathologies. Advances in Multidetector CT imaging technology have enabled additional functionalities, inclu... Read More about MedNeRF: Medical Neural Radiance Fields for Reconstructing 3D-aware CT-Projections from a Single X-ray.
ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction (2023)
Presentation / Conference Contribution
Yu, Z., Haung, S., Fang, C., Breckon, T., & Wang, J. (2023). ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/CVPR52729.2023.01245Reconstructing two hands from monocular RGB images is challenging due to frequent occlusion and mutual confusion. Existing methods mainly learn an entangled representation to encode two interacting hands, which are incredibly fragile to impaired inte... Read More about ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction.
VID-Trans-ReID: Enhanced Video Transformers for Person Re-identification (2022)
Presentation / Conference Contribution
Alsehaim, A., & Breckon, T. (2022). VID-Trans-ReID: Enhanced Video Transformers for Person Re-identification.Video-based person Re-identification (Re-ID) has received increasing attention recently due to its important role within surveillance video analysis. Video-based Re- ID expands upon earlier image-based methods by extracting person features temporally... Read More about VID-Trans-ReID: Enhanced Video Transformers for Person Re-identification.
Amd classification in choroidal oct using hierarchical texton mining (2017)
Presentation / Conference Contribution
Ravenscroft, D., Deng, J., Xie, X., Terry, L., Margrain, T. H., North, R. V., & Wood, A. (2017). Amd classification in choroidal oct using hierarchical texton mining. . https://doi.org/10.1007/978-3-319-70353-4_21
Gamifying Experiential Learning Theory (2023)
Presentation / Conference Contribution
Alsaqqaf, A., & Li, F. W. (in press). Gamifying Experiential Learning Theory. In ICWL 2022, SETE 2022: Learning Technologies and Systems (16-28). https://doi.org/10.1007/978-3-031-33023-0_2
Locating Datacenter Link Faults with a Directed Graph Convolutional Neural Network. (2021)
Presentation / Conference Contribution
Kenning, M. P., Deng, J., Edwards, M., & Xie, X. (2021). Locating Datacenter Link Faults with a Directed Graph Convolutional Neural Network. . https://doi.org/10.5220/0010301403120320
Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation (2023)
Presentation / Conference Contribution
Li, L., Shum, H. P., & Breckon, T. P. (2023). Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/CVPR52729.2023.00903Whilst the availability of 3D LiDAR point cloud data has significantly grown in recent years, annotation remains expensive and time-consuming, leading to a demand for semisupervised semantic segmentation methods with application domains such as auton... Read More about Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation.
Nested shallow cnn-cascade for face detection in the wild (2017)
Presentation / Conference Contribution
Deng, J., & Xie, X. (2017). Nested shallow cnn-cascade for face detection in the wild. . https://doi.org/10.1109/fg.2017.29
3D interactive coronary artery segmentation using random forests and Markov random field optimization (2014)
Presentation / Conference Contribution
Deng, J., Xie, X., Alcock, R., & Roobottom, C. (2014). 3D interactive coronary artery segmentation using random forests and Markov random field optimization. . https://doi.org/10.1109/icip.2014.7025189
Learning feature extractors for AMD classification in OCT using convolutional neural networks (2017)
Presentation / Conference Contribution
Ravenscroft, D., Deng, J., Xie, X., Terry, L., Margrain, T. H., North, R. V., & Wood, A. (2017). Learning feature extractors for AMD classification in OCT using convolutional neural networks. . https://doi.org/10.23919/eusipco.2017.8081167
Combining stacked denoising autoencoders and random forests for face detection (2016)
Presentation / Conference Contribution
Deng, J., Xie, X., & Edwards, M. (2016). Combining stacked denoising autoencoders and random forests for face detection. . https://doi.org/10.1007/978-3-319-48680-2_31
Lossless compression for volumetric medical images using deep neural network with local sampling (2020)
Presentation / Conference Contribution
Nagoor, O. H., Whittle, J., Deng, J., Mora, B., & Jones, M. W. (2020). Lossless compression for volumetric medical images using deep neural network with local sampling. . https://doi.org/10.1109/icip40778.2020.9191031
Age-related macular degeneration detection and stage classification using choroidal oct images (2016)
Presentation / Conference Contribution
Deng, J., Xie, X., Terry, L., Wood, A., White, N., Margrain, T. H., & North, R. V. (2016). Age-related macular degeneration detection and stage classification using choroidal oct images. . https://doi.org/10.1007/978-3-319-41501-7_79
Detect face in the wild using CNN cascade with feature aggregation at multi-resolution (2017)
Presentation / Conference Contribution
Deng, J., & Xie, X. (2017). Detect face in the wild using CNN cascade with feature aggregation at multi-resolution. . https://doi.org/10.1109/icip.2017.8297067
Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery (2022)
Presentation / Conference Contribution
Bhowmik, N., & Breckon, T. (2022). Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery.X-ray baggage security screening is in widespread use and crucial to maintaining transport security for threat/anomaly detection tasks. The automatic detection of anomaly, which is concealed within cluttered and complex electronics/electrical items,... Read More about Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery.
Aesthetic Enhancement via Color Area and Location Awareness (2022)
Presentation / Conference Contribution
Yang, B., Wang, Q., Li, F. W., Liang, X., Wei, T., & Zhu, C. (2022). Aesthetic Enhancement via Color Area and Location Awareness. In Y. Yang, A. D. Parakkat, B. Deng, & S. T. Noh (Eds.), . https://doi.org/10.2312/pg.20221247Choosing a suitable color palette can typically improve image aesthetic, where a naive way is choosing harmonious colors from some pre-defined color combinations in color wheels. However, color palettes only consider the usage of color types without... Read More about Aesthetic Enhancement via Color Area and Location Awareness.