Sampling strategies for learning-based 3D medical image compression
(2022)
Journal Article
Nagoor, O. H., Whittle, J., Deng, J., Mora, B., & Jones, M. W. (2022). Sampling strategies for learning-based 3D medical image compression. Machine Learning with Applications, 8, https://doi.org/10.1016/j.mlwa.2022.100273
Outputs (40)
GRNN: generative regression neural network—a data leakage attack for federated learning (2022)
Journal Article
Ren, H., Deng, J., & Xie, X. (2022). GRNN: generative regression neural network—a data leakage attack for federated learning. ACM Transactions on Intelligent Systems and Technology, 13(4), 1-24. https://doi.org/10.1145/3510032
Joint multi-label learning and feature extraction for temporal link prediction (2022)
Journal Article
Ma, X., Tan, S., Xie, X., Zhong, X., & Deng, J. (2022). Joint multi-label learning and feature extraction for temporal link prediction. Pattern Recognition, 121, https://doi.org/10.1016/j.patcog.2021.108216
MedZip: 3D medical images lossless compressor using recurrent neural network (LSTM) (2021)
Presentation / Conference Contribution
Nagoor, O. H., Whittle, J., Deng, J., Mora, B., & Jones, M. W. (2021, December). MedZip: 3D medical images lossless compressor using recurrent neural network (LSTM). Presented at 2020 25th International Conference on Pattern Recognition (ICPR) IEEE
3D Interactive Segmentation With Semi-Implicit Representation and Active Learning (2021)
Journal Article
Deng, J., & Xie, X. (2021). 3D Interactive Segmentation With Semi-Implicit Representation and Active Learning. IEEE Transactions on Image Processing, 30, 9402-9417. https://doi.org/10.1109/tip.2021.3125491
TLGP: a flexible transfer learning algorithm for gene prioritization based on heterogeneous source domain (2021)
Journal Article
Wang, Y., Xia, Z., Deng, J., Xie, X., Gong, M., & Ma, X. (2021). TLGP: a flexible transfer learning algorithm for gene prioritization based on heterogeneous source domain. BMC Bioinformatics, 22(9), 1-15. https://doi.org/10.1186/s12859-021-04190-9
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, December). Locating Datacenter Link Faults with a Directed Graph Convolutional Neural Network. Presented at ICPRAM
A directed graph convolutional neural network for edge-structured signals in link-fault detection (2021)
Journal Article
Kenning, M., Deng, J., Edwards, M., & Xie, X. (2022). A directed graph convolutional neural network for edge-structured signals in link-fault detection. Pattern Recognition Letters, 153, 100-106. https://doi.org/10.1016/j.patrec.2021.12.003The growing interest in graph deep learning has led to a surge of research focusing on learning various characteristics of graph-structured data. Directed graphs have generally been treated as incidental to definitions on the more general class of un... Read More about A directed graph convolutional neural network for edge-structured signals in link-fault detection.
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, December). Lossless compression for volumetric medical images using deep neural network with local sampling. Presented at 2020 IEEE International Conference on Image Processing (ICIP) IEEE
Learning discriminatory deep clustering models (2019)
Presentation / Conference Contribution
Alqahtani, A., Xie, X., Deng, J., & Jones, M. W. (2019, December). Learning discriminatory deep clustering models. Presented at International Conference on Computer Analysis of Images and Patterns Springer