122 results on '"Humphries, Grant"'
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2. Antarctic Penguin Biogeography Project: Database of abundance and distribution for the Adélie, chinstrap, gentoo, emperor, macaroni and king penguin south of 60 S
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3. Aerial photogrammetry of seabirds from digital aerial video images using relative change in size to estimate flight height
4. A Perspective on the Future of Machine Learning: Moving Away from ‘Business as Usual’ and Towards a Holistic Approach of Global Conservation
5. Machine Learning and ‘The Cloud’ for Natural Resource Applications: Autonomous Online Robots Driving Sustainable Conservation Management Worldwide?
6. Machine Learning Techniques for Quantifying Geographic Variation in Leach’s Storm-Petrel (Hydrobates leucorhous) Vocalizations
7. How the Internet Can Know What You Want Before You Do: Web-Based Machine Learning Applications for Wildlife Management
8. Breaking Away from ‘Traditional’ Uses of Machine Learning: A Case Study Linking Sooty Shearwaters (Ardenna griseus) and Upcoming Changes in the Southern Oscillation Index
9. Machine Learning in Wildlife Biology: Algorithms, Data Issues and Availability, Workflows, Citizen Science, Code Sharing, Metadata and a Brief Historical Perspective
10. Use of Machine Learning (ML) for Predicting and Analyzing Ecological and ‘Presence Only’ Data: An Overview of Applications and a Good Outlook
11. Streaked Shearwaters Calonectris leucomelas of the Korean Peninsula: distribution, status and potential threats
12. Biocontrol of St John’s wort (Hypericum perforatum) provides huge ongoing benefits to New Zealand agriculture
13. Refining seabird marine protected areas by predicting habitat inside foraging range - a case study from the global tropics
14. Antarctic Penguin Biogeography Project: Database of abundance and distribution for the Adélie, chinstrap, gentoo, emperor, macaroni and king penguin south of 60 S
15. Figure 1 from: Che-Castaldo C, Humphries G, Lynch H (2023) Antarctic Penguin Biogeography Project: Database of abundance and distribution for the Adélie, chinstrap, gentoo, emperor, macaroni and king penguin south of 60 S. Biodiversity Data Journal 11: e101476. https://doi.org/10.3897/BDJ.11.e101476
16. Counting animals in aerial images with a density map estimation model
17. Counting animals in aerial images with a density map estimation model
18. The age of the Twitter conference
19. Fortune telling seabirds: sooty shearwaters (Puffinus griseus) predict shifts in Pacific climate
20. Global Issues for, and Profiles of, Arctic Seabird Protection: Effects of Big Oil, New Shipping Lanes, Shifting Baselines, and Climate Change
21. stochLAB: Stochastic Collision Risk Model
22. Putting models to a good use: a rapid assessment of Arctic seabird biodiversity indicates potential conflicts with shipping lanes and human activity
23. Counting animals in aerial images with a crowd counting model
24. Predicting the Foraging Habitats of Sympatrically Breeding Gadfly Petrels in the South Pacific Ocean
25. A first overview of open access digital data for the Ross Sea: complexities, ethics, and management opportunities
26. Spatial predictions of sea surface dimethylsulfide concentrations in the high arctic
27. Aerial photogrammetry of seabirds from digital aerial video images using relative change in size to estimate flight height
28. Seabirds encountered along return transects between South Africa and Antarctica in summer in relation to hydrological features
29. Using Forecasting Methods to Incorporate Social, Economic, and Political Considerations Into Marine Protected Area Planning
30. Using forecasting methods to incorporate social, economic, and political considerations into marine protected area planning
31. Using forecasting methods to incorporate social, economic, and political considerations into Marine Protected Area planning
32. The potential of satellite imagery for surveying whales
33. Predictions of 27 Arctic pelagic seabird distributions using public environmental variables, assessed with colony data: a first digital IPY and GBIF open access synthesis platform
34. The Potential of Satellite Imagery for Surveying Whales
35. Future Directions in Conservation Research on Petrels and Shearwaters
36. Aerial-trained deep learning networks for surveying cetaceans from satellite imagery
37. Future Directions in Conservation Research on Petrels and Shearwaters
38. ESTIMATING STREAKED SHEARWATER CALONECTRIS LEUCOMELAS ABUNDANCE IN THE REPUBLIC OF KOREA USING AUTOMATED ACOUSTIC RECORDERS.
39. Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise
40. Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise
41. BRIDGING THE GAP FROM STUDENT TO SENIOR SCIENTIST : RECOMMENDATIONS FOR ENGAGING EARLY-CAREER SCIENTISTS IN PROFESSIONAL BIOLOGICAL SOCIETIES
42. New Zealand Seabirds : Important Bird Areas and Conservation
43. Still Seeking Moby Dick: Spotting Whales from Space via Satellites, AI.
44. Streaked Shearwaters Calonectris leucomelas of the Korean Peninsula: distribution, status and potential threats.
45. Biocontrol of St John’s wort (<italic>Hypericum perforatum</italic>) provides huge ongoing benefits to New Zealand agriculture.
46. Assessment of Potential Risks from Renewable Energy Development and Other Anthropogenic Factors to Wintering Golden Eagles in the Western United States
47. Landscape Applications of Machine Learning: Comparing Random Forests and Logistic Regression in Multi-Scale Optimized Predictive Modeling of American Marten Occurrence in Northern Idaho, USA
48. Machine Learning for ‘Strategic Conservation and Planning’: Patterns, Applications, Thoughts and Urgently Needed Global Progress for Sustainability
49. Image Recognition in Wildlife Applications
50. ‘Batteries’ in Machine Learning: A First Experimental Assessment of Inference for Siberian Crane Breeding Grounds in the Russian High Arctic Based on ‘Shaving’ 74 Predictors
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