| Bayesian estimation of recent migration rates after a spatial expansion G Hamilton, M Currat, N Ray, G Heckel, M Beaumont, L Excoffier Genetics 170 (1), 409-417, 2005 | 156 | 2005 |
| Molecular analysis reveals tighter social regulation of immigration in patrilocal populations than in matrilocal populations G Hamilton, M Stoneking, L Excoffier Proceedings of the National Academy of Sciences 102 (21), 7476-7480, 2005 | 153 | 2005 |
| Automated detection of koalas using low-level aerial surveillance and machine learning E Corcoran, S Denman, J Hanger, B Wilson, G Hamilton Scientific reports 9 (1), 3208, 2019 | 100 | 2019 |
| Automated detection of wildlife using drones: Synthesis, opportunities and constraints E Corcoran, M Winsen, A Sudholz, G Hamilton Methods in Ecology and Evolution 12 (6), 1103-1114, 2021 | 98 | 2021 |
| An integrated Bayesian network approach to Lyngbya majuscula bloom initiation S Johnson, F Fielding, G Hamilton, K Mengersen Marine environmental research 69 (1), 27-37, 2010 | 86 | 2010 |
| Comment on" Genetic structure of human populations" L Excoffier, G Hamilton Science 300 (5627), 1877-1877, 2003 | 85 | 2003 |
| Investigating the Use of a Bayesian Network to Model the Risk of Lyngbya majuscula Bloom Initiation in Deception Bay, Queensland, Australia GS Hamilton, F Fielding, AW Chiffings, BT Hart, RW Johnstone, ... Human and Ecological Risk Assessment 13 (6), 1271-1287, 2007 | 82 | 2007 |
| Bayesian model averaging for harmful algal bloom prediction G Hamilton, R McVinish, K Mengersen Ecological Applications 19 (7), 1805-1814, 2009 | 48 | 2009 |
| Assessment of crop insect damage using unmanned aerial systems: A machine learning approach E Puig Garcia, F Gonzalez, G Hamilton, P Grundy Proceedings of MODSIM2015, 21st International Congress on Modelling and …, 2015 | 47 | 2015 |
| Learning to fly: integrating spatial ecology with unmanned aerial vehicle surveys PWJ Baxter, G Hamilton Ecosphere 9 (4), e02194, 2018 | 45 | 2018 |
| An approximate Bayesian computation approach for estimating parameters of complex environmental processes in a cellular automata R Rasmussen, G Hamilton Environmental Modelling & Software 29 (1), 1-10, 2012 | 41 | 2012 |
| Habitat heterogeneity influences connectivity in a spatially structured pest population GS Hamilton, PB Mather, JC Wilson Journal of Applied Ecology 43 (2), 219-226, 2006 | 36 | 2006 |
| Evaluating new technology for biodiversity monitoring: Are drone surveys biased? E Corcoran, S Denman, G Hamilton Ecology and Evolution 11 (11), 6649-6656, 2021 | 30 | 2021 |
| Integrating science through Bayesian belief networks: case study of Lyngbya in Moreton Bay G Hamilton, C Alston, T Chiffings, E Abal, B Hart, K Mengersen International Congress on Modelling and Simulation (MODSIM05), 392-399, 2005 | 18 | 2005 |
| New technologies in the mix: Assessing N‐mixture models for abundance estimation using automated detection data from drone surveys E Corcoran, S Denman, G Hamilton Ecology and evolution 10 (15), 8176-8185, 2020 | 16 | 2020 |
| When you can't see the koalas for the trees: Using drones and machine learning in complex environments G Hamilton, E Corcoran, S Denman, ME Hennekam, LP Koh Biological Conservation 247, 108598, 2020 | 16 | 2020 |
| From Science to Management: Using Bayesian Networks to Learn about" Lyngbya" S Johnson, E Abal, K Ahern, G Hamilton Statistical Science, 36-41, 2014 | 16 | 2014 |
| Improving detection probabilities for pests in stored grain D Elmouttie, A Kiermeier, G Hamilton Pest management science 66 (12), 1280-1286, 2010 | 15 | 2010 |
| The ethics of biosurveillance SK Devitt, PWJ Baxter, G Hamilton Journal of Agricultural and Environmental Ethics 32 (5), 709-740, 2019 | 11 | 2019 |
| A comparison of manual and automated detection of rusa deer (Rusa timorensis) from RPAS-derived thermal imagery A Sudholz, S Denman, A Pople, M Brennan, M Amos, G Hamilton Wildlife Research 49 (1), 46-53, 2021 | 9 | 2021 |
Peter BaxterUniversity of Queensland在 uq.edu.au 的电子邮件经过验证
