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Scott C. Chapman
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2020 – today
- 2024
- [j8]Chrisbin James, Daniel Smith, Weigao He, Shekhar S. Chandra, Scott C. Chapman:
GrainPointNet: A deep-learning framework for non-invasive sorghum panicle grain count phenotyping. Comput. Electron. Agric. 217: 108485 (2024) - [c7]Francesca Devoto, Sean Reynolds-Massey-Reed, Cristian Pinzón, Michael Bell, Tim Mclaren, Rakesh Awale, Carlos Camino, Michael Bange, William Woodgate, Scott C. Chapman, Andries B. Potgieter:
Insights in the Ability of High-Resolution Narrow Band Multispectral and Thermal Sensors to Estimate Cotton Production in Australia. IGARSS 2024: 1510-1513 - 2023
- [c6]Andries B. Potgieter, Carlos Camino, Tomas Poblete, X. Zhi, Sean Reynolds-Massey-Reed, Yan Zhao, Anirudh Belwalkar, J. Ruizhu, Barbara George-Jaeggli, Scott C. Chapman, David R. Jordan, A. Wu, Graeme L. Hammer, Pablo J. Zarco-Tejada:
Advances in the Study of Biochemical, Morphological and Physiological Traits of Wheat and Sorghum Crops in Australia Using Hyperspectral Data and Machine Learning. IGARSS 2023: 1952-1955 - 2022
- [c5]Dung Nguyen, Yan Zhao, Yifan Zhang, Anh Ngoc-Lan Huynh, Fred Roosta, Graeme L. Hammer, Scott C. Chapman, Andries B. Potgieter:
Crop Type Prediction Utilising a Long Short-Term Memory with a Self-Attention for Winter Crops in Australia. IGARSS 2022: 2742-2745 - [c4]Sumanta Das, Sean Reynolds Massey-Reed, Jenny Mahuika, James E. M. Watson, Celso Cordova, Loren Otto, Yan Zhao, Scott C. Chapman, Barbara George-Jaeggli, David R. Jordan, Graeme L. Hammer, Andries B. Potgieter:
A High-Throughput Phenotyping Pipeline for Rapid Evaluation of Morphological and Physiological Crop Traits Across Large Fields. IGARSS 2022: 7783-7786 - 2021
- [j7]Pengcheng Hu, Scott C. Chapman, Huidong Jin, Yan Guo, Bangyou Zheng:
Comparison of Modelling Strategies to Estimate Phenotypic Values from an Unmanned Aerial Vehicle with Spectral and Temporal Vegetation Indexes. Remote. Sens. 13(14): 2827 (2021) - [j6]Malini Roy Choudhury, Sumanta Das, Jack Christopher, Armando A. Apan, Scott C. Chapman, Neal W. Menzies, Yash P. Dang:
Improving Biomass and Grain Yield Prediction of Wheat Genotypes on Sodic Soil Using Integrated High-Resolution Multispectral, Hyperspectral, 3D Point Cloud, and Machine Learning Techniques. Remote. Sens. 13(17): 3482 (2021) - [c3]Chrisbin James, Yanyang Gu, Scott C. Chapman, Wei Guo, Etienne David, Simon Madec, Andries B. Potgieter, Anders Eriksson:
Domain Adaptation for Plant Organ Detection with Style Transfer. DICTA 2021: 1-9 - [i2]Etienne David, Mario Serouart, Daniel Smith, Simon Madec, Kaaviya Velumani, Shouyang Liu, Xu Wang, Francisco Pinto Espinosa, Shahameh Shafiee, Izzat S. A. Tahir, Hisashi Tsujimoto, Shuhei Nasuda, Bangyou Zheng, Norbert Kichgessner, Helge Aasen, Andreas Hund, Pouria Sadeghi-Tehran, Koichi Nagasawa, Goro Ishikawa, Sébastien Dandrifosse, Alexis Carlier, Benoit Mercatoris, Ken Kuroki, Haozhou Wang, Masanori Ishii, Minhajul A. Badhon, Curtis Pozniak, David Shaner LeBauer, Morten Lilimo, Jesse Poland, Scott C. Chapman, Benoit de Solan, Frédéric Baret, Ian Stavness, Wei Guo:
Global Wheat Head Dataset 2021: an update to improve the benchmarking wheat head localization with more diversity. CoRR abs/2105.07660 (2021) - 2020
- [i1]Etienne David, Simon Madec, Pouria Sadeghi-Tehran, Helge Aasen, B. Zheng, Shouyang Liu, Norbert Kirchgeßner, Goro Ishikawa, Koichi Nagasawa, Minhajul A. Badhon, Curtis Pozniak, Benoit de Solan, Andreas Hund, Scott C. Chapman, Frédéric Baret, Ian Stavness, Wei Guo:
Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods. CoRR abs/2005.02162 (2020)
2010 – 2019
- 2018
- [c2]Ali Masjedi, Jieqiong Zhao, Addie M. Thompson, Kai-Wei Yang, John E. Flatt, Melba M. Crawford, David S. Ebert, Mitchell R. Tuinstra, Graeme L. Hammer, Scott C. Chapman:
Sorghum Biomass Prediction Using Uav-Based Remote Sensing Data and Crop Model Simulation. IGARSS 2018: 7719-7722 - [c1]Andries B. Potgieter, James E. M. Watson, Mark Eldridge, Kenneth Laws, Barbara George-Jaeggli, Colleen Hunt, Andrew Borrell, Emma Mace, Scott C. Chapman, David R. Jordan, Graeme L. Hammer:
Determining Crop Growth Dynamics in Sorghum Breeding Trials Through Remote and Proximal Sensing Technologies. IGARSS 2018: 8244-8247 - 2017
- [j5]Wei Guo, Bangyou Zheng, Tao Duan, Tokihiro Fukatsu, Scott C. Chapman, Seishi Ninomiya:
EasyPCC: Benchmark Datasets and Tools for High-Throughput Measurement of the Plant Canopy Coverage Ratio under Field Conditions. Sensors 17(4): 798 (2017) - 2016
- [j4]Bangyou Zheng, Edward Holland, Scott C. Chapman:
A standardized workflow to utilise a grid-computing system through advanced message queuing protocols. Environ. Model. Softw. 84: 304-310 (2016) - 2014
- [j3]Dean P. Holzworth, Neil I. Huth, Peter G. de Voil, Eric J. Zurcher, Neville I. Herrmann, Greg McLean, Karine Chenu, Erik J. van Oosterom, Valerie O. Snow, Chris Murphy, Andrew D. Moore, Hamish E. Brown, Jeremy P. M. Whish, Shaun Verrall, Justin Fainges, Lindsay W. Bell, Allan S. Peake, Perry L. Poulton, Zvi Hochman, Peter J. Thorburn, Donald S. Gaydon, Neal P. Dalgliesh, Daniel Rodríguez, Howard Cox, Scott C. Chapman, Alastair Doherty, Edmar I. Teixeira, Joanna Sharp, Rogerio Cichota, Iris Vogeler, Frank Y. Li, Enli Wang, Graeme L. Hammer, Michael J. Robertson, John P. Dimes, Anthony M. Whitbread, James Hunt, Harm van Rees, Tim McClelland, Peter S. Carberry, John N. G. Hargreaves, Neil MacLeoda, Cam McDonald, Justin Harsdorf, Sara Wedgwood, Brian A. Keating:
APSIM - Evolution towards a new generation of agricultural systems simulation. Environ. Model. Softw. 62: 327-350 (2014)
2000 – 2009
- 2002
- [j2]Scott C. Chapman, Peer Schenk, Kemal Kazan, John Manners:
Using biplots to interpret gene expression patterns in plants. Bioinform. 18(1): 202-204 (2002) - [j1]Mark Cooper, Scott C. Chapman, Dean W. Podlich, Graeme L. Hammer:
The GP problem: Quantifying gene-to-phenotype relationships. Silico Biol. 2(2): 151-164 (2002)
Coauthor Index
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