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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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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 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 |
