Scott C Chapman (Scott Chapman)

Publication Activity (10 Years)

Years Active: 2020-2023
Publications (10 Years): 11

Top Topics

Convolutional Neural Network

Optical Coherence Tomography

Top Venues

Plant phenomics (Washington, D.C.)

Scientific data

Journal of experimental botany

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik

This page only lists publications with an associated author ORCID identifier.

Publications

Simon Madec, Kamran Irfan, Kaaviya Velumani, Frederic Baret, Etienne David, Gaetan Daubige, Lucas Bernigaud Samatan, Mario Serouart, Daniel Smith, Chrisbin James, Fernando Camacho, Wei Guo, Benoit De Solan, Scott C Chapman, Marie Weiss
VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation. Scientific data 10 (1) (2023)
Simon Madec, Kamran Irfan, Kaaviya Velumani, Frederic Baret, Etienne David, Gaetan Daubige, Lucas Bernigaud Samatan, Mario Serouart, Daniel Smith, Chrisbin James, Fernando Camacho, Wei Guo, Benoit De Solan, Scott C Chapman, Marie Weiss
VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation. Scientific data 10 (1) (2023)
Simon Madec, Kamran Irfan, Kaaviya Velumani, Frederic Baret, Etienne David, Gaetan Daubige, Lucas Bernigaud Samatan, Mario Serouart, Daniel Smith, Chrisbin James, Fernando Camacho, Wei Guo, Benoit De Solan, Scott C Chapman, Marie Weiss
VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation. Scientific data 10 (1) (2023)
Qiaomin Chen, Bangyou Zheng, Tong Chen, Scott C Chapman
Integrating a crop growth model and radiative transfer model to improve estimation of crop traits based on deep learning. Journal of experimental botany 73 (19) (2022)
Qiaomin Chen, Bangyou Zheng, Karine Chenu, Pengcheng Hu, Scott C Chapman
Unsupervised Plot-Scale LAI Phenotyping via UAV-Based Imaging, Modelling, and Machine Learning. Plant phenomics (Washington, D.C.) 2022 (2022)
Xiaoyu Zhi, Sean Reynolds Massey-Reed, Alex C Wu, Andries B Potgieter, Andrew Borrell, Colleen Hunt, David R Jordan, Yan Zhao, Scott C Chapman, Graeme Hammer, Barbara George-Jaeggli
Estimating Photosynthetic Attributes from High-Throughput Canopy Hyperspectral Sensing in Sorghum. Plant phenomics (Washington, D.C.) 2022 (2022)
Pengcheng Hu, Scott C Chapman, Sivakumar Sukumaran, Matthew Reynolds, Bangyou Zheng
Phenological optimization of late reproductive phase for raising wheat yield potential in irrigated mega-environments. Journal of experimental botany 73 (12) (2022)
Yan Zhao, Bangyou Zheng, Scott C Chapman, Kenneth Laws, Barbara George-Jaeggli, Graeme L Hammer, David R Jordan, Andries B Potgieter
Detecting Sorghum Plant and Head Features from Multispectral UAV Imagery. Plant phenomics (Washington, D.C.) 2021 (2021)
Etienne David, Mario Serouart, Daniel T Smith, Simon Madec, Kaaviya Velumani, Shouyang Liu, Xu Wang, Francisco Pinto, Shahameh Shafiee, Izzat Sidahmed Ali Tahir, Hisashi Tsujimoto, Shuhei Nasuda, Bangyou Zheng, Norbert Kirchgessner, Helge Aasen, Andreas Hund, Pouria Sadhegi-Tehran, Koichi Nagasawa, Goro Ishikawa, Sébastien Dandrifosse, Alexis Carlier, Benjamin Dumont, Benoît Mercatoris, Byron Evers, Ken Kuroki, Haozhou Wang, Masanori Ishii, Minhajul A Badhon, Curtis J Pozniak, David Shaner LeBauer, Morten Lillemo, Jesse A Poland, Scott C Chapman, Benoit de Solan, Frédéric Baret, Ian Stavness, Wei Guo
Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods. Plant phenomics (Washington, D.C.) 2021 (2021)
Daniel T Smith, Andries B Potgieter, Scott C Chapman
Scaling up high-throughput phenotyping for abiotic stress selection in the field. TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik 134 (6) (2021)
Etienne David, Simon Madec, Pouria Sadhegi-Tehran, Helge Aasen, Bangyou Zheng, Shouyang Liu, Norbert Kirchgessner, Goro Ishikawa, Koichi Nagasawa, Minhajul A Badhon, Curtis J 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. Plant phenomics (Washington, D.C.) 2020 (2020)