Zobrazeno 1 - 10
of 100
pro vyhledávání: '"Samuel Foucher"'
Autor:
Alexandre Delplanque, Jérôme Théau, Samuel Foucher, Ghazaleh Serati, Simon Durand, Philippe Lejeune
Publikováno v:
GIScience & Remote Sensing, Vol 61, Iss 1 (2024)
ABSTRACTWildlife surveys are key to assessing the health of global biodiversity. Traditional field and aerial methods however have significant limitations, including high costs, substantial time investment, and potentially biased estimates. The incre
Externí odkaz:
https://doaj.org/article/a45630de654d4fa68e5c6d6cae68e02c
Publikováno v:
Frontiers in Ecology and Evolution, Vol 11 (2023)
As the need to accurately monitor key-species populations grows amid increasing pressures on global biodiversity, the counting of large mammals in savannas has traditionally relied on the Systematic-Reconnaissance-Flight (SRF) technique using light a
Externí odkaz:
https://doaj.org/article/d1b59cd7b55e42ad855eba8af36b896a
Publikováno v:
Remote Sensing, Vol 16, Iss 5, p 818 (2024)
Satellite observations provide critical data for a myriad of applications, but automated information extraction from such vast datasets remains challenging. While artificial intelligence (AI), particularly deep learning methods, offers promising solu
Externí odkaz:
https://doaj.org/article/c62e87f272cd4489920d7496fa72b919
Publikováno v:
Remote Sensing in Ecology and Conservation, Vol 8, Iss 2, Pp 166-179 (2022)
Abstract Survey and monitoring of wildlife populations are among the key elements in nature conservation. The use of unmanned aerial vehicles and light aircrafts as aerial image acquisition systems is growing, as they are cheaper alternatives to trad
Externí odkaz:
https://doaj.org/article/88ca6b128929482f83af51bf74d179cd
Publikováno v:
PLoS ONE, Vol 18, Iss 4, p e0284449 (2023)
The vast amount of images generated by aerial imagery in the context of regular wildlife surveys nowadays require automatic processing tools. At the top of the mountain of different methods to automatically detect objects in images reigns deep learni
Externí odkaz:
https://doaj.org/article/4e41e5e252f2457f9619d77524116b3c
Publikováno v:
Canadian Journal of Remote Sensing, Vol 47, Iss 3, Pp 381-395 (2021)
Airborne LiDAR data allow the precise modeling of topography and are used in multiple contexts. To facilitate further analysis, the point cloud classification process allows the assignment of a class, object or feature, to each point. This research u
Externí odkaz:
https://doaj.org/article/48a30470fa86482ca63edb6b19c22a89
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 6524-6532 (2020)
Two-dimensional phase unwrapping is a critical processing procedure of synthetic aperture radar interferometry. This operation becomes even more difficult in the presence of noise. Both local and global unwrapping algorithms are used in obtaining the
Externí odkaz:
https://doaj.org/article/4c6e64719e4d4e1584b15626830ec303
Publikováno v:
Remote Sensing, Vol 15, Iss 3, p 835 (2023)
The Bidirectional Reflectance Distribution Function (BRDF) defines the anisotropy of surface reflectance and plays a fundamental role in many remote sensing applications. This study proposes a new machine learning-based model for characterizing the B
Externí odkaz:
https://doaj.org/article/40e8ae3876824c488a20082e45d44e3c
Publikováno v:
Canadian Journal of Remote Sensing, Vol 47, Iss 2, Pp 159-161 (2021)
Externí odkaz:
https://doaj.org/article/b2171ce5b1324a548df3f85ea0f490ea
Publikováno v:
Frontiers in Artificial Intelligence, Vol 3 (2020)
Flavescence dorée (FD) is a grapevine disease caused by phytoplasmas and transmitted by leafhoppers that has been spreading in European vineyards despite significant efforts to control it. In this study, we aim to develop a model for the automatic d
Externí odkaz:
https://doaj.org/article/cd2474d3987a42e589f8cb98b9f6deae