Someday we’ll have an app that you can point at a weird bug or unfamiliar fern and have it spit out the genus and species. But right now computer vision systems just aren’t up to the task.

To help things along, researchers have assembled hundreds of thousands of images taken by regular folks of critters in real life situations — and by studying these, our AI helpers may be able to get a handle on biodiversity. For some specialties, we have that already: FaceNet, for instance, is the standard set for learning how to recognize or replicate faces.

But while computers may have trouble recognizing faces, we rarely do — while on the other hand, I can never remember the name of the birds that land on my feeder in the spring. I feel like I know these computer-generated celebrities already Fortunately, I’m not the only one with this problem, and for years the community of the iNaturalist app has been collecting pictures of common and uncommon animals for identification.

And it turns out that these images are the perfect way to teach a system how to recognize plants and animals in the wild. You might think that a computer could learn all it needs to from biology textbooks, field guides and National Geographic.

But when you or I take a picture of a sea lion, it looks a lot different from a professional shot: the background is different, the angle isn’t perfect, the focus is probably off and there may even be other animals in the shot. Even a good computer vision algorithm might not see much in common between the two. Read more from techcrunch.com…

thumbnail courtesy of techcrunch.com