Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Florent Abdelghafour"'
Autor:
Fernanda Leiva, Florent Abdelghafour, Muath Alsheikh, Nina E. Nagy, Jahn Davik, Aakash Chawade
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Common scab (CS) is a major bacterial disease causing lesions on potato tubers, degrading their appearance and reducing their market value. To accurately grade scab-infected potato tubers, this study introduces “ScabyNet”, an image proce
Externí odkaz:
https://doaj.org/article/9da1faaa738d4b13aaa5f0210c3b33a0
Autor:
Belal Gaci, Florent Abdelghafour, Maxime Ryckewaert, Silvia Mas-Garcia, Marine Louargant, Florence Verpont, Yohana Laloum, Aude Moronvalle, Ryad Bendoula, Jean-Michel Roger
Publikováno v:
Data in Brief, Vol 50, Iss , Pp 109532- (2023)
This dataset consists of three groups of hyperspectral images of apple tree plants. The first group of images consists of a temporal monitoring of seven apple tree plants, infected with fire blight (Erwinia amylovora), and six control plants over a p
Externí odkaz:
https://doaj.org/article/da73dfbde68e41d5917e5e470b3bd7e2
Autor:
Florian Rançon, Barna Keresztes, Aymeric Deshayes, Malo Tardif, Florent Abdelghafour, Gael Fontaine, Jean-Pierre Da Costa, Christian Germain
Publikováno v:
Sensors, Vol 23, Iss 2, p 847 (2023)
The potential of image proximal sensing for agricultural applications has been a prolific scientific subject in the recent literature. Its main appeal lies in the sensing of precise information about plant status, which is either harder or impossible
Externí odkaz:
https://doaj.org/article/f4e0488a04514a7aa82e459b9c4c66da
Autor:
Florent Abdelghafour, Barna Keresztes, Aymeric Deshayes, Christian Germain, Jean-Pierre Da Costa
Publikováno v:
Data in Brief, Vol 37, Iss , Pp 107250- (2021)
This article introduces a dataset of high-resolution colour images of grapevines. It contains 99 images acquired in the vineyard from a cruising tractor. Each image includes the full foliage of a grapevine plant. These images display a diverse range
Externí odkaz:
https://doaj.org/article/ce09f929226d4ea7aa9e3a35dcf38622
Publikováno v:
Sensors, Vol 20, Iss 16, p 4380 (2020)
This paper proposes to study the potentialities of on-board colour imaging for the in-field detection of a textbook case disease: the grapevine downy mildew. It introduces an algorithmic strategy for the detection of various forms of foliar symptoms
Externí odkaz:
https://doaj.org/article/1cca92cc300644e3b531e5f887665512
Autor:
Belal Gaci, Silvia Mas Garcia, Florent Abdelghafour, Juliette Adrian, Fabienne Maupas, Jean-Michel Roger
Publikováno v:
Journal of Near Infrared Spectroscopy. 30:122-129
Phenotyping is essential in the process of varietal selection. In the case of sugar beets, richness (g/100g), that is, sugar content, is the key information. The need to acquire this information in a rapid, non-destructive and cheap manner leads the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44ef04dc41f3b5de4c3716c548882a22
https://doi.org/10.1177/09670335221083448
https://doi.org/10.1177/09670335221083448
Autor:
Fanny Prezman, Daniel Moura, Maxime Metz, Florent Abdelghafour, Silvia Mas Mas Garcia, Carole Feilhes, Maxime Ryckewaert, Ryad Bendoula
Publikováno v:
The Analyst. 146(24)
Hyperspectral imaging is an emergent technique in viticulture that can potentially detect bacterial diseases in a non-destructive manner. However, the main problem is to handle the substantial amount of information obtained from this type of data, fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cd889ba682de7f0141ce6aec9a5e23b0
https://pubmed.ncbi.nlm.nih.gov/34821883
https://pubmed.ncbi.nlm.nih.gov/34821883
Publikováno v:
Analytica Chimica Acta
Analytica Chimica Acta, Elsevier Masson, 2021, 1179, ⟨10.1016/j.aca.2021.338823⟩
Analytica Chimica Acta, Elsevier Masson, 2021, 1179, ⟨10.1016/j.aca.2021.338823⟩
International audience; The calibration of Partial Least Square regression (PLSR) models can be disturbed by outlying samples in the data. In these cases the models can be unstable and their predictive potential can be depreciated. To address this pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::636d10fff986b963afc7411184d85d75
https://hal.inrae.fr/hal-03322650
https://hal.inrae.fr/hal-03322650
Autor:
Florent Abdelghafour, Florent Masseglia, Matthieu Lesnoff, Maxime Metz, Jean-Michel Roger, Reza Akbarinia
Publikováno v:
Chemometrics and Intelligent Laboratory Systems
Chemometrics and Intelligent Laboratory Systems, 2020, 203, pp.104076. ⟨10.1016/j.chemolab.2020.104076⟩
Chemometrics and Intelligent Laboratory Systems, Elsevier, 2020, 203, pp.104076. ⟨10.1016/j.chemolab.2020.104076⟩
Chemometrics and Intelligent Laboratory Systems, 2020, 203, pp.104076. ⟨10.1016/j.chemolab.2020.104076⟩
Chemometrics and Intelligent Laboratory Systems, Elsevier, 2020, 203, pp.104076. ⟨10.1016/j.chemolab.2020.104076⟩
International audience; A well known issue regarding PLS lies in the difficulty to apprehend nonlinearities. As a solution, an extension of the method, “KNN-PLS”, was developed. However, this solution is based on a neighbourhood selection algorit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::abcaa074223d9ee97f8177602b2f17b6
https://hal.inrae.fr/hal-02899789/document
https://hal.inrae.fr/hal-02899789/document
Autor:
Aymeric Deshayes, Barna Keresztes, Florent Abdelghafour, Jean-Pierre da Costa, Christian Germain
Publikováno v:
Data in Brief
Data in Brief, Elsevier, 2021, 37, pp.107250. ⟨10.1016/j.dib.2021.107250⟩
Data in Brief, Vol 37, Iss, Pp 107250-(2021)
Data in Brief, Elsevier, 2021, 37, pp.107250. ⟨10.1016/j.dib.2021.107250⟩
Data in Brief, Vol 37, Iss, Pp 107250-(2021)
International audience; This article introduces a dataset of high-resolution colour images of grapevines. It contains 99 images acquired in the vineyard from a cruising tractor. Each image includes the full foliage of a grapevine plant. These images
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1838953917058b9e5b71518f63f54f13
https://doi.org/10.1016/j.dib.2021.107250
https://doi.org/10.1016/j.dib.2021.107250