LemurFaceID Builds a Database of the Madagascar Mammals
References: mediarelations.gwu.edu & digitaltrends
LemurFaceID is a new piece of software designed to help the population of lemurs on Madagascar, the huge tropical island off the eastern coast of Africa. Using similar neural network-based facial recognition systems that have become more and more common in many different pieces of software that work on human faces, LemurFaceID is designed to build a database of the mammals and to help track them less invasively.
For conservationists, tracking populations of species is essential. After all, it's very difficult to keep tabs of the rise and fall in the health of a given species if researchers can't lock in on the specific members of that species. However, conservationists also need to be careful to leave the animals relatively undisturbed while tracking them. LemurFaceID fits perfectly into that middle ground, tracking lemurs through cameras rather than with tags.
For conservationists, tracking populations of species is essential. After all, it's very difficult to keep tabs of the rise and fall in the health of a given species if researchers can't lock in on the specific members of that species. However, conservationists also need to be careful to leave the animals relatively undisturbed while tracking them. LemurFaceID fits perfectly into that middle ground, tracking lemurs through cameras rather than with tags.
Trend Themes
1. Facial Recognition for Wildlife Conservation - Developing facial recognition software for non-human species can aid in conservation efforts by allowing for less invasive tracking methods.
2. Adapting Human Technologies for Animal Research - Applying neural network-based facial recognition systems commonly used in human research can improve conservation efforts for animals.
3. Expanding Facial Recognition Usage Across Species - Using facial recognition technology to identify and track various species beyond humans can open up new opportunities for wildlife research and conservation.
Industry Implications
1. Wildlife Conservation - Adopting facial recognition and other advanced technologies can revolutionize the field of wildlife conservation and improve tracking methods.
2. Software Development - Developing unique software solutions tailored specifically to certain types of research, such as facial recognition software for wildlife tracking, can be a lucrative market with room for innovation.
3. Camera and Imaging Technology - Improving camera and imaging technology can enable more effective tracking methods using artificial intelligence, especially in the field of wildlife conservation and research.
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