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2025

Journal Article

Spatioformer: A Geo-encoded Transformer for Large-Scale Plant Species Richness Prediction

Guo, Yiqing, Mokany, Karel, Levick, Shaun R., Yang, Jinyan and Moghadam, Peyman (2025). Spatioformer: A Geo-encoded Transformer for Large-Scale Plant Species Richness Prediction. IEEE Transactions on Geoscience and Remote Sensing, 63 4403216, 1-1. doi: 10.1109/tgrs.2025.3534654

Spatioformer: A Geo-encoded Transformer for Large-Scale Plant Species Richness Prediction

2024

Journal Article

Uncertainty propagation in the internet of things

Pal, Shantanu, Khalifa, Sara, Miller, Dimity, Dedeoglu, Volkan, Dorri, Ali, Ramachandran, Gowri, Moghadam, Peyman, Kusy, Brano and Jurdak, Raja (2024). Uncertainty propagation in the internet of things. Discover Internet of Things, 4 (1) 32. doi: 10.1007/s43926-024-00085-2

Uncertainty propagation in the internet of things

2024

Journal Article

Multivariate prototype representation for domain-generalized incremental learning

Peng, Can, Koniusz, Piotr, Guo, Kaiyu, Lovell, Brian C. and Moghadam, Peyman (2024). Multivariate prototype representation for domain-generalized incremental learning. Computer Vision and Image Understanding, 249 104215, 104215. doi: 10.1016/j.cviu.2024.104215

Multivariate prototype representation for domain-generalized incremental learning

2024

Journal Article

WildScenes: A benchmark for 2D and 3D semantic segmentation in large-scale natural environments

Vidanapathirana, Kavisha, Knights, Joshua, Hausler, Stephen, Cox, Mark, Ramezani, Milad, Jooste, Jason, Griffiths, Ethan, Mohamed, Shaheer, Sridharan, Sridha, Fookes, Clinton and Moghadam, Peyman (2024). WildScenes: A benchmark for 2D and 3D semantic segmentation in large-scale natural environments. The International Journal of Robotics Research, 44 (4), 532-549. doi: 10.1177/02783649241278369

WildScenes: A benchmark for 2D and 3D semantic segmentation in large-scale natural environments

2024

Journal Article

Graph neural networks-enhanced relation prediction for ecotoxicology (GRAPE)

Anand, Gaurangi, Koniusz, Piotr, Kumar, Anupama, Golding, Lisa A., Morgan, Matthew J. and Moghadam, Peyman (2024). Graph neural networks-enhanced relation prediction for ecotoxicology (GRAPE). Journal of Hazardous Materials, 472 134456. doi: 10.1016/j.jhazmat.2024.134456

Graph neural networks-enhanced relation prediction for ecotoxicology (GRAPE)

2024

Conference Publication

Reg-NF: Efficient Registration of Implicit Surfaces within Neural Fields

Hausler, Stephen, Hall, David, Mahendren, Sutharsan and Moghadam, Peyman (2024). Reg-NF: Efficient Registration of Implicit Surfaces within Neural Fields. 2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, 13-17 May 2024. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/icra57147.2024.10610982

Reg-NF: Efficient Registration of Implicit Surfaces within Neural Fields

2024

Conference Publication

TULIP: transformer for upsampling of LiDAR point clouds

Yang, Bin, Pfreundschuhl, Patrick, Siegwartl, Roland, Hutter, Marco, Moghadam, Peyman and Patil, Vaishakh (2024). TULIP: transformer for upsampling of LiDAR point clouds. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, United States, 16-22 June 2024. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/CVPR52733.2024.01454

TULIP: transformer for upsampling of LiDAR point clouds

2023

Journal Article

FactoFormer: factorized hyperspectral transformers with self-supervised pre-training

Mohamed, Shaheer, Haghighat, Maryam, Fernando, Tharindu, Sridharan, Sridha, Fookes, Clinton and Moghadam, Peyman (2023). FactoFormer: factorized hyperspectral transformers with self-supervised pre-training. IEEE Transactions on Geoscience and Remote Sensing, 62 5501614, 1-1. doi: 10.1109/tgrs.2023.3343392

FactoFormer: factorized hyperspectral transformers with self-supervised pre-training

2023

Journal Article

Pose-graph attentional graph neural network for lidar place recognition

Ramezani, Milad, Wang, Liang, Knights, Joshua, Li, Zhibin, Pounds, Pauline and Moghadam, Peyman (2023). Pose-graph attentional graph neural network for lidar place recognition. IEEE Robotics and Automation Letters, 9 (2), 1182-1189. doi: 10.1109/lra.2023.3341766

Pose-graph attentional graph neural network for lidar place recognition

2023

Journal Article

GeoAdapt: self-supervised test-time adaptation in LiDAR place recognition using geometric priors

Knights, Joshua, Hausler, Stephen, Sridharan, Sridha, Fookes, Clinton and Moghadam, Peyman (2023). GeoAdapt: self-supervised test-time adaptation in LiDAR place recognition using geometric priors. IEEE Robotics and Automation Letters, PP (99) 3337698, 915-922. doi: 10.1109/lra.2023.3337698

GeoAdapt: self-supervised test-time adaptation in LiDAR place recognition using geometric priors

2023

Journal Article

CL3: generalization of contrastive loss for lifelong learning

Roy, Kaushik, Simon, Christian, Moghadam, Peyman and Harandi, Mehrtash (2023). CL3: generalization of contrastive loss for lifelong learning. Journal of Imaging, 9 (12) 259, 1-16. doi: 10.3390/jimaging9120259

CL3: generalization of contrastive loss for lifelong learning

2023

Journal Article

Exploiting field dependencies for learning on categorical data

Li, Zhibin, Koniusz, Piotr, Zhang, Lu, Pagendam, Daniel Edward and Moghadam, Peyman (2023). Exploiting field dependencies for learning on categorical data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45 (11), 13509-13522. doi: 10.1109/tpami.2023.3298028

Exploiting field dependencies for learning on categorical data

2023

Conference Publication

Uncertainty-aware lidar place recognition in novel environments

Mason, Keita, Knights, Joshua, Ramezani, Milad, Moghadam, Peyman and Miller, Dimity (2023). Uncertainty-aware lidar place recognition in novel environments. 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Detroit, MI United States, 1 - 5 October 2023. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/iros55552.2023.10341383

Uncertainty-aware lidar place recognition in novel environments

2023

Journal Article

Subspace distillation for continual learning

Roy, Kaushik, Simon, Christian, Moghadam, Peyman and Harandi, Mehrtash (2023). Subspace distillation for continual learning. Neural Networks, 167, 65-79. doi: 10.1016/j.neunet.2023.07.047

Subspace distillation for continual learning

2023

Conference Publication

Deep robust multi-robot re-localisation in natural environments

Ramezani, Milad, Griffiths, Ethan, Haghighat, Maryam, Pitt, Alex and Moghadam, Peyman (2023). Deep robust multi-robot re-localisation in natural environments. 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Detroit, MI United States, 1 - 5 October 2023. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/iros55552.2023.10341798

Deep robust multi-robot re-localisation in natural environments

2023

Conference Publication

Measuring situational awareness latency in human-robot teaming experiments

Senaratne, Hashini, Pitt, Alex, Talbot, Fletcher, Moghadam, Peyman, Sikka, Pavan, Howard, David, Williams, Jason, Kulić, Dana and Paris, Cécile (2023). Measuring situational awareness latency in human-robot teaming experiments. 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), Busan, South Korea, 28-31 August 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ro-man57019.2023.10309377

Measuring situational awareness latency in human-robot teaming experiments

2023

Conference Publication

Learning partial correlation based deep visual representation for image classification

Rahman, Saimunur, Koniusz, Piotr, Wang, Lei, Zhou, Luping, Moghadam, Peyman and Sun, Changming (2023). Learning partial correlation based deep visual representation for image classification. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, BC Canada, 17-24 June 2023. Washington, DC United States: IEEE Computer Society. doi: 10.1109/cvpr52729.2023.00603

Learning partial correlation based deep visual representation for image classification

2023

Conference Publication

Wild-places: a large-scale dataset for lidar place recognition in unstructured natural environments

Knights, Joshua, Vidanapathirana, Kavisha, Ramezani, Milad, Sridharan, Sridha, Fookes, Clinton and Moghadam, Peyman (2023). Wild-places: a large-scale dataset for lidar place recognition in unstructured natural environments. 2023 IEEE International Conference on Robotics and Automation (ICRA), London, United Kingdom, 29 May - 2 June 2023. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/icra48891.2023.10160432

Wild-places: a large-scale dataset for lidar place recognition in unstructured natural environments

2023

Journal Article

Spectral geometric verification: re-ranking point cloud retrieval for metric localization

Vidanapathirana, Kavisha, Moghadam, Peyman, Sridharan, Sridha and Fookes, Clinton (2023). Spectral geometric verification: re-ranking point cloud retrieval for metric localization. IEEE Robotics and Automation Letters, 8 (5), 2494-2501. doi: 10.1109/lra.2023.3255560

Spectral geometric verification: re-ranking point cloud retrieval for metric localization

2023

Journal Article

Plant species richness prediction from DESIS hyperspectral data: a comparison study on feature extraction procedures and regression models

Guo, Yiqing, Mokany, Karel, Ong, Cindy, Moghadam, Peyman, Ferrier, Simon and Levick, Shaun R. (2023). Plant species richness prediction from DESIS hyperspectral data: a comparison study on feature extraction procedures and regression models. ISPRS Journal of Photogrammetry and Remote Sensing, 196, 120-133. doi: 10.1016/j.isprsjprs.2022.12.028

Plant species richness prediction from DESIS hyperspectral data: a comparison study on feature extraction procedures and regression models