Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Benoit de Solan"'
Autor:
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
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-12 (2023)
Abstract Applying deep learning to images of cropping systems provides new knowledge and insights in research and commercial applications. Semantic segmentation or pixel-wise classification, of RGB images acquired at the ground level, into vegetation
Externí odkaz:
https://doaj.org/article/d871935e9b3345a89a6132b6706b11b6
Autor:
Etienne David, Franklin Ogidi, Daniel Smith, Scott Chapman, Benoit de Solan, Wei Guo, Frederic Baret, Ian Stavness
Publikováno v:
Plant Phenomics, Vol 5 (2023)
Data competitions have become a popular approach to crowdsource new data analysis methods for general and specialized data science problems. Data competitions have a rich history in plant phenotyping, and new outdoor field datasets have the potential
Externí odkaz:
https://doaj.org/article/0c1fc606ae874d47997060bf0571fa5a
Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images
Autor:
Mario Serouart, Raul Lopez-Lozano, Gaëtan Daubige, Maëva Baumont, Brigitte Escale, Benoit De Solan, Frédéric Baret
Publikováno v:
Plant Phenomics, Vol 5 (2023)
The sowing pattern has an important impact on light interception efficiency in maize by determining the spatial distribution of leaves within the canopy. Leaves orientation is an important architectural trait determining maize canopies light intercep
Externí odkaz:
https://doaj.org/article/7651d36ea8e84578a78c6dc7d819c58b
Autor:
Etienne David, Mario Serouart, Daniel Smith, Simon Madec, Kaaviya Velumani, Shouyang Liu, Xu Wang, Francisco Pinto, Shahameh Shafiee, Izzat S. A. 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, Benoit Mercatoris, Byron Evers, Ken Kuroki, Haozhou Wang, Masanori Ishii, Minhajul A. Badhon, Curtis Pozniak, David Shaner LeBauer, Morten Lillemo, Jesse Poland, Scott Chapman, Benoit de Solan, Frédéric Baret, Ian Stavness, Wei Guo
Publikováno v:
Plant Phenomics, Vol 2021 (2021)
The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in
Externí odkaz:
https://doaj.org/article/acd6363f47b04262b456b55f5e2a3ba9
Autor:
Etienne David, Simon Madec, Pouria Sadeghi-Tehran, Helge Aasen, Bangyou 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
Publikováno v:
Plant Phenomics, Vol 2020 (2020)
The detection of wheat heads in plant images is an important task for estimating pertinent wheat traits including head population density and head characteristics such as health, size, maturity stage, and the presence of awns. Several studies have de
Externí odkaz:
https://doaj.org/article/3499e8909968470bbafa59490f8097e3
Architectural Response of Wheat Cultivars to Row Spacing Reveals Altered Perception of Plant Density
Publikováno v:
Frontiers in Plant Science, Vol 10 (2019)
Achieving novel improvements in crop management may require changing interrow distance in cultivated fields. Such changes would benefit from a better understanding of plant responses to the spatial heterogeneity in their environment. Our work investi
Externí odkaz:
https://doaj.org/article/36364c2e09a04451bcd4b7b02260a261
Publikováno v:
Plant Phenomics, Vol 2019 (2019)
Total above-ground biomass at harvest and ear density are two important traits that characterize wheat genotypes. Two experiments were carried out in two different sites where several genotypes were grown under contrasted irrigation and nitrogen trea
Externí odkaz:
https://doaj.org/article/86e956f065cd4c6c97af4e4e0f40f003
Autor:
Philippe Burger, Alexis Comar, Etienne David, Gaëtan Daubige, Benoit de Solan, François Joudelat, Frédéric Baret
Progresses in agronomy rely on accurate measurement of the experimentations conducted to improve the yield component. Measurement of the plant density is required for a number of applications since it drives part of the crop fate. The standard manual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a8b74efecca13d4300e470c1da6e419f
https://doi.org/10.1101/2021.04.27.441631
https://doi.org/10.1101/2021.04.27.441631
Autor:
Xiuliang Jin, Simon Madec, Frédéric Baret, Shouyang Liu, Emmanuelle Heritier, Benoit de Solan, Florent Duyme, Hao Lu
Publikováno v:
Agricultural and Forest Meteorology
Agricultural and Forest Meteorology, Elsevier Masson, 2019, 264, pp.225-234. ⟨10.1016/j.agrformet.2018.10.013⟩
Agricultural and Forest Meteorology, Elsevier Masson, 2019, 264, pp.225-234. ⟨10.1016/j.agrformet.2018.10.013⟩
International audience; Wheat ear density estimation is an appealing trait for plant breeders. Current manual counting is tedious and inefficient. In this study we investigated the potential of convolutional neural networks (CNNs) to provide accurate
Autor:
Mélinda Boukhana, Joris Ravaglia, Franck Hétroy Wheeler, Frédéric Larue, Benoit de Solan, Eric Casella
Publikováno v:
Journées Françaises d'Informatique Graphique
Journées Françaises d'Informatique Graphique, Nov 2020, Nancy, France
HAL
Journées Françaises d'Informatique Graphique, Nov 2020, Nancy, France
HAL
National audience; Measuring leaf areas is a critical task in plant biology. Automatic leaf area estimation from a 3D point cloud is usually done via meshing techniques or parametric surface modeling. However, there is currently no consensus on the b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::2abf74ba7d0e53946e01c27f1f322071
https://hal.archives-ouvertes.fr/hal-03256446
https://hal.archives-ouvertes.fr/hal-03256446