Difference between revisions of "Animal Ecology"
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* [http://www.nextgov.com/emerging-tech/2020/02/noaa-use-microsoft-ai-advance-protection-endangered-species/163208/ NOAA to Use Microsoft AI to Advance Protection of Endangered Species | Brandi Vincent - Nextgov] | * [http://www.nextgov.com/emerging-tech/2020/02/noaa-use-microsoft-ai-advance-protection-endangered-species/163208/ NOAA to Use Microsoft AI to Advance Protection of Endangered Species | Brandi Vincent - Nextgov] | ||
* [http://deepmind.com/blog/article/using-machine-learning-to-accelerate-ecological-research Using machine learning to accelerate ecological research | S. Petersen, M. Palmer, U. Paquet, and P. Kohli - Deepmind] | * [http://deepmind.com/blog/article/using-machine-learning-to-accelerate-ecological-research Using machine learning to accelerate ecological research | S. Petersen, M. Palmer, U. Paquet, and P. Kohli - Deepmind] | ||
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| + | Animal ecology concerns the relationships of individuals to their environments, including physical factors and other organisms, and the consequences of these relationships for evolution, population growth and regulation, interactions between species, the composition of biological communities, and energy flow and nutrient cycling through the ecosystem. From the standpoint of population, the individual organism is the fundamental unit of ecology. Factors influencing the survival and reproductive success of individuals form the basis for under-standing population processes. [ | ||
| + | http://www.encyclopedia.com/social-sciences/encyclopedias-almanacs-transcripts-and-maps/animal-ecology | Encyclopedia.com] | ||
There is increasing demand for efficient ways to process large volumes of data from visual-based remote-technology, such as unmanned aerial vehicles (UAVs) in ecology and conservation, with machine learning methods representing a promising avenue to address varying user demands. Here, we evaluated current trends in how machine learning and UAVs are used to process imagery data for detecting animals and vegetation across habitats, placing emphasis on their utility for endangered species. [http://www.int-res.com/abstracts/esr/v39/p91-104/ Importance of machine learning for enhancing ecological studies using information-rich imagery | Antoine M. Dujon, Gail Schofield] | There is increasing demand for efficient ways to process large volumes of data from visual-based remote-technology, such as unmanned aerial vehicles (UAVs) in ecology and conservation, with machine learning methods representing a promising avenue to address varying user demands. Here, we evaluated current trends in how machine learning and UAVs are used to process imagery data for detecting animals and vegetation across habitats, placing emphasis on their utility for endangered species. [http://www.int-res.com/abstracts/esr/v39/p91-104/ Importance of machine learning for enhancing ecological studies using information-rich imagery | Antoine M. Dujon, Gail Schofield] | ||
Revision as of 06:48, 20 February 2020
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- Case Studies
- NOAA to Use Microsoft AI to Advance Protection of Endangered Species | Brandi Vincent - Nextgov
- Using machine learning to accelerate ecological research | S. Petersen, M. Palmer, U. Paquet, and P. Kohli - Deepmind
Animal ecology concerns the relationships of individuals to their environments, including physical factors and other organisms, and the consequences of these relationships for evolution, population growth and regulation, interactions between species, the composition of biological communities, and energy flow and nutrient cycling through the ecosystem. From the standpoint of population, the individual organism is the fundamental unit of ecology. Factors influencing the survival and reproductive success of individuals form the basis for under-standing population processes. [ http://www.encyclopedia.com/social-sciences/encyclopedias-almanacs-transcripts-and-maps/animal-ecology | Encyclopedia.com]
There is increasing demand for efficient ways to process large volumes of data from visual-based remote-technology, such as unmanned aerial vehicles (UAVs) in ecology and conservation, with machine learning methods representing a promising avenue to address varying user demands. Here, we evaluated current trends in how machine learning and UAVs are used to process imagery data for detecting animals and vegetation across habitats, placing emphasis on their utility for endangered species. Importance of machine learning for enhancing ecological studies using information-rich imagery | Antoine M. Dujon, Gail Schofield
