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2025 Conference Publication Inductive graph few-shot class incremental learningLi, Yayong, Moghadam, Peyman, Peng, Can, Ye, Nan and Koniusz, Piotr (2025). Inductive graph few-shot class incremental learning. 18th International Conference on Web Search and Data Mining-WSDM, Hannover, Germany, 10-14 March 2025. New York, NY, United States: ACM. doi: 10.1145/3701551.3703578 |
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2025 Journal Article WildScenes: A benchmark for 2D and 3D semantic segmentation in large-scale natural environmentsVidanapathirana, Kavisha, Knights, Joshua, Hausler, Stephen, Cox, Mark, Ramezani, Milad, Jooste, Jason, Griffiths, Ethan, Mohamed, Shaheer, Sridharan, Sridha, Fookes, Clinton and Moghadam, Peyman (2025). 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 |
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2025 Journal Article Spatioformer: A Geo-encoded Transformer for Large-Scale Plant Species Richness PredictionGuo, 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 |
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2024 Journal Article Uncertainty propagation in the internet of thingsPal, 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 |
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2024 Conference Publication Spectral-enhanced transformers: leveraging large-scale pretrained models for hyperspectral object trackingMohamed, Shaheer, Fernando, Tharindu, Sridharan, Sridha, Moghadam, Peyman and Fookes, Clinton (2024). Spectral-enhanced transformers: leveraging large-scale pretrained models for hyperspectral object tracking. 2024 14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Helsinki, Finland, 9-11 December 2024. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/whispers65427.2024.10876537 |
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2024 Journal Article Multivariate prototype representation for domain-generalized incremental learningPeng, 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 |
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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 |
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2024 Conference Publication Reg-NF: Efficient Registration of Implicit Surfaces within Neural FieldsHausler, 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 |
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2024 Conference Publication TULIP: transformer for upsampling of LiDAR point cloudsYang, 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 |
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2023 Journal Article FactoFormer: factorized hyperspectral transformers with self-supervised pre-trainingMohamed, 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 |
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2023 Journal Article Pose-graph attentional graph neural network for lidar place recognitionRamezani, 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 |
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2023 Journal Article GeoAdapt: self-supervised test-time adaptation in LiDAR place recognition using geometric priorsKnights, 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 |
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2023 Journal Article CL3: generalization of contrastive loss for lifelong learningRoy, 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 |
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2023 Journal Article Exploiting field dependencies for learning on categorical dataLi, 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 |
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2023 Conference Publication Uncertainty-aware lidar place recognition in novel environmentsMason, 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 |
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2023 Journal Article Subspace distillation for continual learningRoy, 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 |
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2023 Conference Publication Deep robust multi-robot re-localisation in natural environmentsRamezani, 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 |
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2023 Conference Publication Measuring situational awareness latency in human-robot teaming experimentsSenaratne, 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 |
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2023 Conference Publication Learning partial correlation based deep visual representation for image classificationRahman, 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 |
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2023 Conference Publication Wild-places: a large-scale dataset for lidar place recognition in unstructured natural environmentsKnights, 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 |
