By Professor Maurice Pagnucco

Conference Papers

Delgrande JP; Lakemeyer G; Pagnucco M; Sack J, 2025, 'Belief Revision in a Probabilistic Setting', in Proceedings of the TwentySecond International Conference on Principles of Knowledge Representation and Reasoning, International Joint Conferences on Artificial Intelligence Organization, pp. 250 - 259, presented at 22nd International Conference on Principles of Knowledge Representation and Reasoning {KR-2025}, 11 November 2025 - 17 November 2025, http://dx.doi.org/10.24963/kr.2025/25

Yan S; Liu S; Ieva AD; Pagnucco M; Song Y, 2025, 'Source-free Few-shot Segmentation for Rarer Brain Tumors', in 2025 International Joint Conference on Neural Networks (IJCNN), IEEE, pp. 1 - 8, presented at 2025 International Joint Conference on Neural Networks (IJCNN), 30 June 2025 - 05 July 2025, http://dx.doi.org/10.1109/ijcnn64981.2025.11228625

Zhu Z; Fan L; Pagnucco M; Song Y, 2025, 'Interpretable Image Classification via Non-parametric Part Prototype Learning', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 9762 - 9771, http://dx.doi.org/10.1109/CVPR52734.2025.00912

Fan L; Fan D; Hu Z; Ding Y; Di D; Yi K; Pagnucco M; Song Y, 2025, 'MANTA: A Large-Scale Multi-View and Visual-Text Anomaly Detection Dataset for Tiny Objects', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 25518 - 25527, http://dx.doi.org/10.1109/CVPR52734.2025.02376

Gao S; Baker MAB; Pagnucco M; Song Y, 2025, 'Multimodal Weakly Supervised Segmentation for Histopathology', in Proceedings International Symposium on Biomedical Imaging, http://dx.doi.org/10.1109/ISBI60581.2025.10980775

Tang Q; Fan L; Pagnucco M; Song Y, 2025, 'Prototype-Based Image Prompting for Weakly Supervised Histopathological Image Segmentation', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 30271 - 30280, http://dx.doi.org/10.1109/CVPR52734.2025.02818

Fu Y; Tompkins A; Song Y; Pagnucco M, 2025, 'Structure based SAT dataset for analysing GNN generalisation', in Proceedings of Machine Learning Research, pp. 4834 - 4842

Zhong H; Song W; Pagnucco M; Song Y, 2025, 'SynerGuard: A Robust Framework for Point Cloud Classification via Local Geometry and Spatial Topology', in Proceedings IEEE International Conference on Robotics and Automation, pp. 9582 - 9589, http://dx.doi.org/10.1109/ICRA55743.2025.11127583

Cong C; Xuan S; Liu S; Zhang S; Pagnucco M; Song Y, 2024, 'Decoupled Optimisation for Long-Tailed Visual Recognition', in Proceedings of the Aaai Conference on Artificial Intelligence, pp. 1380 - 1388, http://dx.doi.org/10.1609/aaai.v38i2.27902

Limarga R; Song Y; Pagnucco M; Rajaratnam D, 2024, 'Epistemic Reasoning in Computational Machine Ethics', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 82 - 94, http://dx.doi.org/10.1007/978-981-99-8391-9_7

Gao J; Blair A; Pagnucco M, 2024, 'Explainable Visual Question Answering via Hybrid Neural-Logical Reasoning', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN60899.2024.10651165

Limarga R; Song Y; Nayak A; Rajaratnam D; Pagnucco M, 2024, 'Formalisation and Evaluation of Properties for Consequentialist Machine Ethics', in Ijcai International Joint Conference on Artificial Intelligence, pp. 440 - 448

Sun B; Pagnucco M; Song Y, 2024, 'Fully Distributed, Flexible Compositional Visual Representations via Soft Tensor Products', in Advances in Neural Information Processing Systems

Yan S; Liu S; Di Ieva A; Pagnucco M; Song Y, 2024, 'Meta-Transfer Learning for Few-Shot Meningioma Segmentation', in Proceedings International Symposium on Biomedical Imaging, http://dx.doi.org/10.1109/ISBI56570.2024.10635194

Fan L; Ding Y; Pagnucco M; Song Y, 2024, 'PATCH-WISE AUGMENTATION FOR ANOMALY DETECTION AND LOCALIZATION', in ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, pp. 5425 - 5429, http://dx.doi.org/10.1109/ICASSP48485.2024.10446994

Wang Y; Pagnucco M; Song Y, 2024, 'Self-training with Domain-Mixed Data for Few-Shot Domain Adaptation in Medical Image Segmentation Tasks', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 299 - 309, http://dx.doi.org/10.1007/978-3-031-45673-2_30

Heng Z; Pagnucco M; Meijering E; Song Y, 2024, 'Vascular Topology Rectification Network for Automated Retinal Artery/Vein Segmentation', in Proceedings International Symposium on Biomedical Imaging, http://dx.doi.org/10.1109/ISBI56570.2024.10635229

Xu Y; Guo R; Pagnucco M; Song Y, 2023, 'Draw2Edit: Mask-Free Sketch-Guided Image Manipulation', in Mm 2023 Proceedings of the 31st ACM International Conference on Multimedia, pp. 7205 - 7215, http://dx.doi.org/10.1145/3581783.3612398

Huang R; Tompkins A; Pagnucco M; Song Y, 2023, 'Towards Single Source Domain Generalisation in Trajectory Prediction: A Motion Prior based Approach', in Proceedings of Machine Learning Research, McGill University, Montréal, Québec, Canada, pp. 227 - 243, presented at Conference on Lifelong Learning Agents, 22-25 August 2023,, McGill University, Montréal, Québec, Canada, 22 August 2023 - 25 August 2023, https://proceedings.mlr.press/v232/huang23a.html

Gao J; Blair A; Pagnucco M, 2023, 'A Symbolic-Neural Reasoning Model for Visual Question Answering', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN54540.2023.10191538

Qian S; Pagnucco M; Song Y, 2023, 'Adaptive Local Prototype and Cycle Attention for Few-shot Medical Image Segmentation', in 2023 International Conference on Digital Image Computing Techniques and Applications Dicta 2023, pp. 49 - 56, http://dx.doi.org/10.1109/DICTA60407.2023.00016

Wan F; Wang J; Duan H; Song Y; Pagnucco M; Long Y, 2023, 'Community-Aware Federated Video Summarization', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN54540.2023.10191101

Huang R; Pagnucco M; Song Y, 2023, 'HyperTraj: Towards Simple and Fast Scene-Compliant Endpoint Conditioned Trajectory Prediction', in IEEE International Conference on Intelligent Robots and Systems, pp. 3208 - 3213, http://dx.doi.org/10.1109/IROS55552.2023.10341647

Gao J; Blair A; Wu Q; Pagnucco M, 2023, 'LoRA: A Logical Reasoning Augmented Dataset for Visual Question Answering', in Advances in Neural Information Processing Systems

Wang J; Sun Z; Qian Y; Gong D; Sun X; Lin M; Pagnucco M; Song Y, 2023, 'MAXIMIZING SPATIO-TEMPORAL ENTROPY OF DEEP 3D CNNS FOR EFFICIENT VIDEO RECOGNITION', in 11th International Conference on Learning Representations Iclr 2023

Huang R; Pagnucco M; Song Y, 2022, 'Analysis of the Over-exposure Problem for Robust Scene Parsing', in 2022 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, pp. 1 - 8, presented at 2022 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 30 November 2022 - 02 December 2022, http://dx.doi.org/10.1109/dicta56598.2022.10034628

Xie K; Zhong H; Chang J; Pagnucco M; Song Y, 2022, 'D2E2-Net: Double Deep Edge Enhancement for Weakly-Supervised Cell Nuclei Segmentation with Incomplete Point Annotations', in 2022 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, pp. 1 - 8, presented at 2022 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 30 November 2022 - 02 December 2022, http://dx.doi.org/10.1109/dicta56598.2022.10034599

Wang J; Qin L; Zhang P; Long Y; Hu B; Pagnucco M; Wang S; Song Y, 2022, 'Towards Unified Multi-Excitation for Unsupervised Video Prediction', in BMVC 2022 - 33rd British Machine Vision Conference Proceedings, London, UK & Online, presented at BMVC 2022 - 33rd British Machine Vision Conference, London, UK & Online, 21 November 2022, https://bmvc2022.mpi-inf.mpg.de/587/

Xie K; Yang Y; Pagnucco M; Song Y, 2022, 'Electron Microscope Image Registration Using Laplacian Sharpening Transformer U-Net', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Singapore, pp. 310 - 319, presented at 25th International Conference, Medical Image Computing and Computer Assisted Intervention, MICCAI 2022, Singapore, 18 September 2022 - 22 September 2022, http://dx.doi.org/10.1007/978-3-031-16446-0_30

Foo G; Kara S; Pagnucco M, 2022, 'Challenges of robotic disassembly in practice', in Procedia CIRP, Leuven, Belgium, pp. 513 - 518, presented at 29th CIRP Life Cycle Engineering Conference, Leuven, Belgium, 04 April 2022, http://dx.doi.org/10.1016/j.procir.2022.02.085

Cong C; Yang Y; Liu S; Pagnucco M; Di Ieva A; Berkovsky S; Song Y, 2022, 'Adaptive Unified Contrastive Learning for Imbalanced Classification', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 348 - 357, http://dx.doi.org/10.1007/978-3-031-21014-3_36

Li P; Yang Y; Pagnucco M; Song Y, 2022, 'CoGNet: Cooperative Graph Neural Networks', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN55064.2022.9892241

Delgrande JP; Sack J; Lakemeyer G; Pagnucco M, 2022, 'Epistemic Logic of Likelihood and Belief', in Ijcai International Joint Conference on Artificial Intelligence, pp. 2599 - 2605, http://dx.doi.org/10.24963/ijcai.2022/360

Fan L; Ding Y; Fan D; Di D; Pagnucco M; Song Y, 2022, 'GrainSpace: A Large-scale Dataset for Fine-grained and Domain-adaptive Recognition of Cereal Grains', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 21084 - 21093, http://dx.doi.org/10.1109/CVPR52688.2022.02044

Li L; Pagnucco M; Song Y, 2022, 'Graph-based Spatial Transformer with Memory Replay for Multi-future Pedestrian Trajectory Prediction', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 2221 - 2231, http://dx.doi.org/10.1109/CVPR52688.2022.00227

Cong C; Yang Y; Liu S; Pagnucco M; Song Y, 2022, 'Imbalanced Histopathology Image Classification Using Deep Feature Graph Attention Network', in Proceedings International Symposium on Biomedical Imaging, http://dx.doi.org/10.1109/ISBI52829.2022.9761619

Luo S; Heng Z; Pagnucco M; Song Y, 2022, 'Two-Stage Topological Refinement Network for Retinal Artery/Vein Classification', in Proceedings International Symposium on Biomedical Imaging, http://dx.doi.org/10.1109/ISBI52829.2022.9761669

Wang J; Long Y; Pagnucco M; Song Y, 2021, 'Dynamic Graph Warping Transformer for Video Alignment', in 32nd British Machine Vision Conference, BMVC 2021, Virtual, presented at 32nd British Machine Vision Conference, BMVC 2021, Virtual, 22 November 2021, https://www.bmvc2021-virtualconference.com/conference/papers/paper_0993.html

Bai Y; Wang J; Long Y; Hu B; Song Y; Pagnucco M; Guan Y, 2021, 'Discriminative Latent Semantic Graph for Video Captioning', in Mm 2021 Proceedings of the 29th ACM International Conference on Multimedia, pp. 3556 - 3564, http://dx.doi.org/10.1145/3474085.3475519

Pagnucco M; Rajaratnam D; Limarga R; Nayak A; Song Y, 2021, 'Epistemic Reasoning for Machine Ethics with Situation Calculus', in Aies 2021 Proceedings of the 2021 Aaai ACM Conference on AI Ethics and Society, pp. 814 - 821, http://dx.doi.org/10.1145/3461702.3462586

Lin H; Pagnucco M; Song Y, 2021, 'Edge guided progressively generative image outpainting', in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 806 - 815, http://dx.doi.org/10.1109/CVPRW53098.2021.00090

Cong C; Liu S; Ieva AD; Pagnucco M; Berkovsky S; Song Y, 2021, 'Texture enhanced generative adversarial network for stain normalisation in histopathology images', in Proceedings International Symposium on Biomedical Imaging, pp. 1949 - 1952, http://dx.doi.org/10.1109/ISBI48211.2021.9433860

Foo G; Kara S; Pagnucco M, 2021, 'Screw detection for disassembly of electronic waste using reasoning and re-training of a deep learning model', in Procedia CIRP, pp. 666 - 671, http://dx.doi.org/10.1016/j.procir.2021.01.172

Cong C; Yang Z; Song Y; Pagnucco M, 2020, 'Towards Enforcing Social Distancing Regulations with Occlusion-Aware Crowd Detection', in 16th IEEE International Conference on Control Automation Robotics and Vision Icarcv 2020, pp. 297 - 302, http://dx.doi.org/10.1109/ICARCV50220.2020.9305507

Xiao Y; Silvera D; Pagnucco M, 2020, 'Autonomous Behaviour Planning for Socially-Assistive Robots in Therapy and Education', Australia, presented at Australasian Conference on Robotics and Automation, Australia, 08 December 2020

Huang R; Song Y; Pagnucco M, 2020, 'An Improved Discriminator for GAN-Based Trajectory Prediction Models', in 2020 Digital Image Computing Techniques and Applications Dicta 2020, http://dx.doi.org/10.1109/DICTA51227.2020.9363414

Limarga R; Pagnucco M; Song Y; Nayak A, 2020, 'Non-monotonic Reasoning for Machine Ethics with Situation Calculus', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 203 - 215, http://dx.doi.org/10.1007/978-3-030-64984-5_16

Trofimova A; Wiley T; Pagnucco M; Velonaki M, 2019, 'Exploring human machine-mediated interaction for applications in social HRI', in ACM International Conference Proceeding Series, Association for Computing Machinery (ACM), AUSTRALIA, UX Machines Pty Ltd, pp. 347 - 351, presented at Proceedings of the 31st Australian Conference on Human-Computer-Interaction, AUSTRALIA, UX Machines Pty Ltd, 02 December 2019 - 05 December 2019, http://dx.doi.org/10.1145/3369457.3369492

Schwering C; Pagnucco M, 2019, 'A representation theorem for reasoning in first-order multi-agent knowledge bases', in Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, Montreal, Canada, pp. 926 - 934, presented at AAMAS, Montreal, Canada, 13 May 2019 - 17 May 2019

Rajaratnam D; Hengst B; Pagnucco M; Sammut C; Thielscher M, 2016, 'Composability in cognitive hierarchies', in Kang BH; Bai Q (ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Nature, Hobart, TAS, Australia, pp. 42 - 55, presented at 29th Australasian Joint Conference, Hobart, TAS, Australia, 05 December 2016 - 08 December 2016, http://dx.doi.org/10.1007/978-3-319-50127-7_4

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