We hear more and more success in the use of artificial neural networks. Here they paint pictures, here they write poetry. Creative and self-taught, won't they soon take up our work?
Trained on cats
New uses for artificial neural networks are emerging more and more. Here is an example of the last days. Nvidia engineer Robert Bond has created an automatic system to deal with the neighbour's cats, who love to invade his property without demand. The animals marking their territory and screaming at night were very annoying for the engineer. Now, as soon as a cat appears on the site, the system detects it and turns on water sprayers that scare the animal away.
You ask, what does the neural network have to do with it? Well, then try to explain to the computer what a cat is and what it looks like. It was a cat, and not any other animal that accidentally entered its site. Not a dog or an accidental crow, and even less so Bond himself, who went out to his site, although at first he also got it from the watering pads.
The artificial neural network Caffe plays a key role in this anti-chelation system. It is tasked with determining who exactly the visitor to the lawn is. With the help of a camera, the security system monitors all movements in the protected area. As soon as an unidentified object appears on the lawn, it is photographed and its images are transmitted to the Jetson TX1 - a hardware module from Nvidia, which is also designed for image recognition. If the neural network detects that there is a cat in the photographs, the closest sprinkler immediately turns on, which scares the animal away. But in the future, unless, of course, animal defenders stop the inventive engineer, Bond hopes to create a system that would shoot water at cats with an aim.
Can the system be configured for dogs, or, for example, only for ginger cats? Can. The advantage of neural networks is that they do not need to "verbally" explain what a cat is. She just needs a lot of pictures of these animals - the so-called training set. The network itself finds features in images that are characteristic of cats and remembers them. This is learning. Now that the network is trained, it will be able to recognize the cat in the images.
By the way, you can try the Caffe neural network, created by scientists from the University of California at Berkeley, in action, and see how it distinguishes cats from dogs, at /demo.caffe.berkeleyvision.org/. Upload an image or paste a link to it and the system will tell you what is shown in the image.
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