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2026 Other Outputs Sorghum diversity head counting datasetKarannagoda, Rukshan, Baktashmotlagh, Mahsa, Chapman, Scott, Wang, Zijian, Guo, Kaiyu, Luo, Yadan, James, Chrisbin and Zheng, Bangyou (2026). Sorghum diversity head counting dataset. The University of Queensland. (Dataset) doi: 10.48610/45beb77 |
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2025 Other Outputs 3D imaging and deep learning for phenotyping sorghum at canopy scaleJames, Chrisbin (2025). 3D imaging and deep learning for phenotyping sorghum at canopy scale. PhD Thesis, School of Agriculture and Food Sustainability, The University of Queensland. doi: 10.14264/8f857fe |
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2025 Conference Publication Evaluating neural kernel surface reconstruction for extracting mesh geometry from pointclouds for volumetric analysis of sorghum paniclesJames, Chrisbin, Chapman, Scott C. and Chandra, Shekhar S. (2025). Evaluating neural kernel surface reconstruction for extracting mesh geometry from pointclouds for volumetric analysis of sorghum panicles. 2025 International Geoscience and Remote Sensing Symposium-IGARSS-Annual, Brisbane, QLD, Australia, 3-8 August 2025. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/igarss55030.2025.11242439 |
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2025 Journal Article A scalable and efficient UAV-based pipeline and deep learning framework for phenotyping sorghum panicle morphology from point cloudsJames, Chrisbin, Chandra, Shekhar S. and Chapman, Scott C. (2025). A scalable and efficient UAV-based pipeline and deep learning framework for phenotyping sorghum panicle morphology from point clouds. Plant Phenomics, 7 (2) 100050, 1-19. doi: 10.1016/j.plaphe.2025.100050 |
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2025 Other Outputs 2024 Scott Teaching TrialGho Brito, Carla, Chapman, Scott, Smith, Daniel, Chen, Xiaolong, James, Chris, MUGAMBA, Edward, Oya, Riku and Cave, Lleyton (2025). 2024 Scott Teaching Trial. The University of Queensland. (Dataset) doi: 10.48610/808c370 |
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2024 Journal Article GrainPointNet: a deep-learning framework for non-invasive sorghum panicle grain count phenotypingJames, Chrisbin, Smith, Daniel, He, Weigao, Chandra, Shekhar S. and Chapman, Scott C. (2024). GrainPointNet: a deep-learning framework for non-invasive sorghum panicle grain count phenotyping. Computers and Electronics in Agriculture, 217 108485, 108485. doi: 10.1016/j.compag.2023.108485 |
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2023 Journal Article VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentationMadec, Simon, Irfan, Kamran, Velumani, Kaaviya, Baret, Frederic, David, Etienne, Daubige, Gaetan, Samatan, Lucas Bernigaud, Serouart, Mario, Smith, Daniel, James, Chrisbin, Camacho, Fernando, Guo, Wei, De Solan, Benoit, Chapman, Scott C. and Weiss, Marie (2023). VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation. Scientific Data, 10 (1) 302, 1-12. doi: 10.1038/s41597-023-02098-y |
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2023 Other Outputs Wheat Head Detection Ground-UAV DatasetChapman, Scott and James, Chris (2023). Wheat Head Detection Ground-UAV Dataset. The University of Queensland. (Dataset) doi: 10.48610/f6a6b07 |
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2023 Journal Article From prototype to inference: a pipeline to apply deep learning in sorghum panicle detectionJames, Chrisbin, Gu, Yanyang, Potgieter, Andries, David, Etienne, Madec, Simon, Guo, Wei, Baret, Frédéric, Eriksson, Anders and Chapman, Scott (2023). From prototype to inference: a pipeline to apply deep learning in sorghum panicle detection. Plant Phenomics, 5 0017, 1-16. doi: 10.34133/plantphenomics.0017 |
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2023 Other Outputs Sorghum Panicle Detection Ground-UAV DatasetChapman, Scott and James, Chris (2023). Sorghum Panicle Detection Ground-UAV Dataset. The University of Queensland, Grains Research and Development Corporation (GRDC). (Dataset) doi: 10.48610/9c3dd16 |
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2021 Conference Publication Domain adaptation for plant organ detection with style transferJames, Chrisbin, Gu, Yanyang, Chapman, Scott, Guo, Wei, David, Etienne, Madec, Simon, Potgieter, Andries and Eriksson, Anders (2021). Domain adaptation for plant organ detection with style transfer. International Conference on Digital Image Computing - Techniques and Applications (DICTA), Online, 29 November - 1 December 2021. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/DICTA52665.2021.9647293 |
