By Professor Maurice Pagnucco

Book Chapters

Xu Y; Pagnucco M; Song Y, 2023, 'DHG-GAN: Diverse Image Outpainting via Decoupled High Frequency Semantics', in Computer Vision – ACCV 2022, Springer Nature Switzerland, pp. 168 - 184, http://dx.doi.org/10.1007/978-3-031-26293-7_11

Guo R; Pagnucco M; Song Y, 2021, 'Learning with Noise: Mask-Guided Attention Model for Weakly Supervised Nuclei Segmentation', in Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, Springer International Publishing, pp. 461 - 470, http://dx.doi.org/10.1007/978-3-030-87196-3_43

Cong C; Liu S; Di Ieva A; Pagnucco M; Berkovsky S; Song Y, 2021, 'Semi-supervised Adversarial Learning for Stain Normalisation in Histopathology Images', in Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, Springer International Publishing, pp. 581 - 591, http://dx.doi.org/10.1007/978-3-030-87237-3_56

Ashar J; Ashmore J; Hall B; Harris S; Hengst B; Liu R; Mei Z; Pagnucco M; Roy R; Sammut C; Sushkov O; Teh B; Tsekouras L, 2015, 'RoboCup SPL 2014 Champion Team Paper', in RoboCup 2014: Robot World Cup XVIII, Springer International Publishing, pp. 70 - 81, http://dx.doi.org/10.1007/978-3-319-18615-3_6

Heap B; Pagnucco M, 2013, 'Repeated Sequential Single-Cluster Auctions with Dynamic Tasks for Multi-Robot Task Allocation with Pickup and Delivery', in Multiagent System Technologies, Springer Berlin Heidelberg, pp. 87 - 100, http://dx.doi.org/10.1007/978-3-642-40776-5_10

Vongbunyong S; Kara S; Pagnucco M, 2012, 'A Framework for Using Cognitive Robotics in Disassembly Automation', in Leveraging Technology for a Sustainable World, Springer Berlin Heidelberg, pp. 173 - 178, http://dx.doi.org/10.1007/978-3-642-29069-5_30

Pagnucco M, 2006, 'Isaac Levi on abduction', in Knowledge and inquiry, Cambridge university press, New York, pp. 143 - 156, http://dx.doi.org/10.1017/CBO9780511584312.012

Pagnucco M; Foo N, 1993, 'Inverting resolution with conceptual graphs', in Conceptual Graphs for Knowledge Representation, Springer Berlin Heidelberg, pp. 238 - 253, http://dx.doi.org/10.1007/3-540-56979-0_13

Journal articles

Xu Y; Pagnucco M; Song Y, 2023, 'An edge guided coarse-to-fine generative network for image outpainting', Neurocomputing, 541, pp. 126254 - 126254, http://dx.doi.org/10.1016/j.neucom.2023.126254

Guo R; Xie K; Pagnucco M; Song Y, 2023, 'SAC-Net: Learning with weak and noisy labels in histopathology image segmentation', Medical Image Analysis, 86, pp. 102790, http://dx.doi.org/10.1016/j.media.2023.102790

Foo G; Kara S; Pagnucco M, 2023, 'Artificial Learning for Part Identification in Robotic Disassembly Through Automatic Rule Generation in an Ontology', IEEE Transactions on Automation Science and Engineering, 20, pp. 296 - 309, http://dx.doi.org/10.1109/TASE.2022.3149242

Wang W; Pagnucco M; Xu C; Song Y, 2023, 'InterREC: An Interpretable Method for Referring Expression Comprehension', IEEE Transactions on Multimedia, pp. 1 - 13, http://dx.doi.org/10.1109/TMM.2023.3251111

Yang Z; Cong C; Pagnucco M; Song Y, 2023, 'Multi-scale multi-reception attention network for bone age assessment in X-ray images', Neural Networks, 158, pp. 249 - 257, http://dx.doi.org/10.1016/j.neunet.2022.11.002

Cong C; Liu S; Di Ieva A; Pagnucco M; Berkovsky S; Song Y, 2022, 'Colour adaptive generative networks for stain normalisation of histopathology images', Medical Image Analysis, 82, pp. 102580, http://dx.doi.org/10.1016/j.media.2022.102580

Chen WH; Foo G; Kara S; Pagnucco M, 2021, 'Automated generation and execution of disassembly actions', Robotics and Computer-Integrated Manufacturing, 68, http://dx.doi.org/10.1016/j.rcim.2020.102056

Foo G; Kara S; Pagnucco M, 2021, 'An ontology-based method for semi-automatic disassembly of lcd monitors and unexpected product types', International Journal of Automation Technology, 15, pp. 168 - 181, http://dx.doi.org/10.20965/IJAT.2021.P0168

Chen WH; Foo G; Kara S; Pagnucco M, 2020, 'Application of a multi-head tool for robotic disassembly', Procedia CIRP, 90, pp. 630 - 635, http://dx.doi.org/10.1016/j.procir.2020.02.047

Rezvani M; Rajaratnam D; Ignjatovic A; Pagnucco M; Jha S, 2019, 'Analyzing XACML policies using answer set programming', International Journal of Information Security, 18, pp. 465 - 479, http://dx.doi.org/10.1007/s10207-018-0421-5

Zhuang Z; Pagnucco M; Zhang Y, 2017, 'Inter-Definability of Horn Contraction and Horn Revision', Journal of Philosophical Logic, 46, pp. 299 - 332, http://dx.doi.org/10.1007/s10992-016-9401-2

Schwering C; Pagnucco M; Lakemeyer G, 2017, 'Belief revision and projection in the epistemic situation calculus', Artificial Intelligence, 251, pp. 62 - 97, http://dx.doi.org/10.1016/j.artint.2017.07.004

Kara S; Vongbunyong S; Pagnucco M, 2016, 'Vision-based execution monitoring of state transition in disassembly automation', International Journal of Automation Technology, 10, pp. 708 - 716, http://dx.doi.org/10.20965/ijat.2016.p0708

Vongbunyong S; Kara S; Pagnucco M, 2015, 'Learning and revision in cognitive robotics disassembly automation', Robotics and Computer-Integrated Manufacturing, 34, pp. 79 - 94, http://dx.doi.org/10.1016/j.rcim.2014.11.003

Nakata NM; Hamacher DW; Warren J; Byrne A; Pagnucco M; Harley R; Venugopal S; Thorpe K; Neville R; Bolt R, 2014, 'Using Modern Technologies to Capture and Share Indigenous Astronomical Knowledge', Australian Academic & Research Libraries, 45, pp. 101 - 110, http://dx.doi.org/10.1080/00048623.2014.917786

Zhuang Z; Pagnucco M, 2014, 'Entrenchment-Based Horn Contraction', JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 51, pp. 227 - 254, http://dx.doi.org/10.1613/jair.4430

Vongbunyong S; Kara S; Pagnucco M, 2013, 'Application of cognitive robotics in disassembly of products', CIRP Annals - Manufacturing Technology, 62, pp. 31 - 34, http://dx.doi.org/10.1016/j.cirp.2013.03.037

Vongbunyong S; Kara S; Pagnucco M, 2013, 'Basic behaviour control of the vision-based cognitive robotic disassembly automation', Assembly Automation, 33, pp. 38 - 56, http://dx.doi.org/10.1108/01445151311294694

Burgard W; Konolige K; Pagnucco M; Vassos S, 2012, 'AAAI Workshop - Technical Report: Preface', AAAI Workshop - Technical Report, WS-12-06

Shapiro S; Pagnucco M; Lesperance Y; Levesque HJ, 2011, 'Iterated belief change in the situation calculus', Artificial Intelligence, 175, pp. 165 - 192, http://dx.doi.org/10.1016/j.artint.2010.04.003

Delgrande J; Nayak A; Pagnucco M, 2005, 'Gricean belief change', Studia Logica, 79(1), pp. 97 - 113, http://dx.doi.org/10.1007/s11225-005-0496-7

Nayak A; Pagnucco M; Peppas P, 2003, 'Dynamic Belief Revision Operators', Artificial Intelligence, 146(2), pp. 193 - 228, http://dx.doi.org/10.1016/S0004-3702(03)00017-1

Pagnucco M; Peppas P, 2001, 'Causality and minimal change demystified', IJCAI International Joint Conference on Artificial Intelligence, pp. 125 - 130

Pagnucco M; Jauregui V; Foo N, 2001, 'A Trajectory Approach to Causality', Studia Logica, 67, pp. 385 - 401, http://dx.doi.org/10.1023/A:1010564432183

Rott H; Pagnucco M, 1999, 'Severe withdrawal (and recovery)', Journal of Philosophical Logic, 28, pp. 501 - 547, http://dx.doi.org/10.1023/A:1004344003217

Conference Papers

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, IEEE, presented at 2023 International Joint Conference on Neural Networks (IJCNN), 18 June 2023 - 23 June 2023, http://dx.doi.org/10.1109/IJCNN54540.2023.10191538

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, IEEE, presented at 2023 International Joint Conference on Neural Networks (IJCNN), 18 June 2023 - 23 June 2023, http://dx.doi.org/10.1109/IJCNN54540.2023.10191101

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, 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, 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

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), Springer Nature Switzerland, 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, Elsevier BV, 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

Delgrande JP; Sack J; Lakemeyer G; Pagnucco M, 2022, 'Epistemic Logic of Likelihood and Belief', in IJCAI International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, pp. 2599 - 2605, presented at Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}, 23 July 2022 - 29 July 2022, 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, IEEE, pp. 21084 - 21093, presented at 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 18 June 2022 - 24 June 2022, 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, IEEE, pp. 2221 - 2231, presented at 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 18 June 2022 - 24 June 2022, http://dx.doi.org/10.1109/CVPR52688.2022.00227

Li P; Yang Y; Pagnucco M; Song Y, 2022, 'CoGNet: Cooperative Graph Neural Networks', in Proceedings of the International Joint Conference on Neural Networks, IEEE, presented at 2022 International Joint Conference on Neural Networks (IJCNN), 18 July 2022 - 23 July 2022, http://dx.doi.org/10.1109/IJCNN55064.2022.9892241

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), Springer Nature Switzerland, pp. 348 - 357, http://dx.doi.org/10.1007/978-3-031-21014-3_36

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

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, ACM, pp. 3556 - 3564, presented at MM '21: ACM Multimedia Conference, 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, ACM, pp. 814 - 821, presented at AIES '21: AAAI/ACM Conference on AI, Ethics, and Society, 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, IEEE, pp. 1949 - 1952, presented at 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 13 April 2021 - 16 April 2021, http://dx.doi.org/10.1109/ISBI48211.2021.9433860

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