Artikelen met mandaten voor openbare toegang - Ethan WhiteMeer informatie
Ergens beschikbaar: 57
Best practices for scientific computing
G Wilson, DA Aruliah, CT Brown, NP Chue Hong, M Davis, RT Guy, ...
PLoS biology 12 (1), e1001745, 2014
Mandaten: US National Institutes of Health, UK Engineering and Physical Sciences …
Iterative near-term ecological forecasting: Needs, opportunities, and challenges
MC Dietze, A Fox, LM Beck-Johnson, JL Betancourt, MB Hooten, ...
Proceedings of the National Academy of Sciences 115 (7), 1424-1432, 2018
Mandaten: US National Science Foundation, Gordon and Betty Moore Foundation
BioTIME: A database of biodiversity time series for the Anthropocene
M Dornelas, LH Antao, F Moyes, AE Bates, AE Magurran, D Adam, ...
Global Ecology and Biogeography 27 (7), 760-786, 2018
Mandaten: US National Science Foundation, US Department of Agriculture, Gordon and …
Individual tree-crown detection in RGB imagery using semi-supervised deep learning neural networks
BG Weinstein, S Marconi, S Bohlman, A Zare, E White
Remote Sensing 11 (11), 1309, 2019
Mandaten: US Department of Agriculture, Gordon and Betty Moore Foundation, German …
Cross-site learning in deep learning RGB tree crown detection
BG Weinstein, S Marconi, SA Bohlman, A Zare, EP White
Ecological Informatics 56, 101061, 2020
Mandaten: US National Science Foundation, US Department of Agriculture, Gordon and …
An extensive comparison of species-abundance distribution models
E Baldridge, DJ Harris, X Xiao, EP White
PeerJ 4, e2823, 2016
Mandaten: US National Science Foundation
Taking species abundance distributions beyond individuals
H Morlon, EP White, RS Etienne, JL Green, A Ostling, D Alonso, ...
Ecology Letters 12 (6), 488-501, 2009
Mandaten: John D. and Catherine T. MacArthur Foundation
Skills and knowledge for data-intensive environmental research
SE Hampton, MB Jones, LA Wasser, MP Schildhauer, SR Supp, J Brun, ...
BioScience 67 (6), 546-557, 2017
Mandaten: US National Science Foundation, US Department of Energy, Gordon and Betty …
DeepForest: A Python package for RGB deep learning tree crown delineation
BG Weinstein, S Marconi, M Aubry‐Kientz, G Vincent, H Senyondo, ...
Methods in Ecology and Evolution 11 (12), 1743-1751, 2020
Mandaten: US National Science Foundation, Gordon and Betty Moore Foundation
Developing an automated iterative near‐term forecasting system for an ecological study
EP White, GM Yenni, SD Taylor, EM Christensen, EK Bledsoe, JL Simonis, ...
Methods in Ecology and Evolution 10 (3), 332-344, 2019
Mandaten: US National Science Foundation, Gordon and Betty Moore Foundation
A strong test of the maximum entropy theory of ecology
X Xiao, DJ McGlinn, EP White
The American Naturalist 185 (3), E70-E80, 2015
Mandaten: John D. and Catherine T. MacArthur Foundation
No general relationship between mass and temperature in endothermic species
K Riemer, RP Guralnick, EP White
Elife 7, e27166, 2018
Mandaten: US National Science Foundation, Gordon and Betty Moore Foundation
The prevalence and impact of transient species in ecological communities
SJ Snell Taylor, BS Evans, EP White, AH Hurlbert
Ecology 99 (8), 1825-1835, 2018
Mandaten: US National Science Foundation, Gordon and Betty Moore Foundation
A remote sensing derived data set of 100 million individual tree crowns for the National Ecological Observatory Network
BG Weinstein, S Marconi, SA Bohlman, A Zare, A Singh, SJ Graves, ...
Elife 10, e62922, 2021
Mandaten: US National Science Foundation, US Department of Agriculture, Gordon and …
Forecasting biodiversity in breeding birds using best practices
DJ Harris, SD Taylor, EP White
PeerJ 6, e4278, 2018
Mandaten: Gordon and Betty Moore Foundation
Developing a modern data workflow for regularly updated data
GM Yenni, EM Christensen, EK Bledsoe, SR Supp, RM Diaz, EP White, ...
PLoS Biology 17 (1), e3000125, 2019
Mandaten: US National Science Foundation, Gordon and Betty Moore Foundation
Continental-scale hyperspectral tree species classification in the United States National Ecological Observatory Network
S Marconi, BG Weinstein, S Zou, SA Bohlman, A Zare, A Singh, D Stewart, ...
Remote Sensing of Environment 282, 113264, 2022
Mandaten: US National Science Foundation, US Department of Agriculture, Gordon and …
A general deep learning model for bird detection in high‐resolution airborne imagery
BG Weinstein, L Garner, VR Saccomanno, A Steinkraus, A Ortega, ...
Ecological Applications 32 (8), e2694, 2022
Mandaten: US Department of Defense, Gordon and Betty Moore Foundation
A data science challenge for converting airborne remote sensing data into ecological information
S Marconi, SJ Graves, D Gong, MS Nia, M Le Bras, BJ Dorr, P Fontana, ...
PeerJ 6, e5843, 2019
Mandaten: US National Science Foundation, US Department of Energy, US Department of …
Comparison of large‐scale citizen science data and long‐term study data for phenology modeling
SD Taylor, JM Meiners, K Riemer, MC Orr, EP White
Ecology 100 (2), e02568, 2019
Mandaten: US National Science Foundation, US Department of Agriculture, Gordon and …
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