In an effort to help protect and conserve endangered species, scientists have been tracking and tagging them for years. However, there are some species that are either too large in population or too sensitive to tagging, and researchers have been working on another way to track them.
Now, thanks to SLOOP, a new computer vision software program from MIT, identifying animals has never been easier. A human sorting through 10,000 images would likely take years to properly identify animals, but this computer program cuts down the manpower and does things much quicker. Through the use of pattern-recognition algorithms, the program is able to match up stripes and spots on an animal and return 20 images that are likely matches, giving researchers a much smaller and more accurate pool to work with. Then the researchers turn to crowdsourcing, and with the aid of adept pattern-matchers, are able to narrow things down even more, resulting in 97% accuracy. This will allow researchers to spend more practical time in the field working on conversation efforts instead of wasting time in front of a computer screen.