In a world where everything you see is a computer generated image, dogs are no different.

They are not just computers.

Dogs have eyes, too.

A human’s eyes have sensors that capture their gaze and respond accordingly to our facial expressions.

But unlike computers, dogs have eyes that respond to the sounds and sights of the world around them, too, and respond differently to stimuli from their environment than humans do.

That means that dogs can see better than people.

Now, scientists at the Max Planck Institute for Human Cognitive and Brain Sciences in Germany have developed a computer vision algorithm that can help dogs track their environment and learn about their surroundings.

“We think that this algorithm can be used to solve the challenge of understanding the human eye,” says Andreas E. Schäfer, a computer scientist at the Institute.

He and his team developed an algorithm that takes into account the differences in human and dog vision, and it can also analyze the human visual environment and determine if a dog is looking at a target or another object.

This algorithm can then be used by a dog to find and locate objects or people.

The algorithm can detect a dog’s proximity to objects with different degrees of accuracy.

Dogs can also use this algorithm to distinguish between humans and other dogs.

This technology can also be used for human-to-dog communication, for example.

The Max Planks researchers are working on improving the algorithm and making it better.

The goal is to create a computer that can detect dogs from 100 feet away and, if it detects a dog that is about 100 feet from the human, it will recognize that dog as a dog and respond with its own unique response.

“This is the first time that we have been able to create an algorithm with this kind of specificity,” says Einat Rachid, a researcher at the German Federal Institute of Technology (Berlin) and one of the Max-Planck researchers.

Rachids and his colleagues are currently working on building an algorithm for a new type of human-dog interaction, known as “dog-to–human communication.”

For this new type, dogs can communicate with each other through a series of “hits” in order to form a human-like relationship.

The dogs are then able to interact with each human in a more natural way.

They use their bodies to make contact with the human’s body.

“In order to create human-scale dog-to.human communication, we need to take advantage of dogs’ natural sense of smell,” Rachis says.

In this way, the dog’s sense of touch can be amplified.

The researchers hope to see if the algorithm can learn to distinguish the different types of touch in humans.

“There is a great need for this technology in human- and dog-sensing applications,” Schäffler says.

The German research group is now working on an application for the dogs to track their owners, such as to detect where they are.

“The algorithm can help us to understand the relationships between dogs and humans, to learn about human-dogs interactions, to help humans understand the differences between dogs, and to learn the human behavior of dogs,” Ritzen says.

He hopes that the new technology can eventually be used in a human environment, such a classroom.

The research has been published in Science Advances.