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Or if there were a person standing in the middle of the highway with a big sign covering his or her face, the self-driving car would just drive through because it didn't see the person's face and thus recognize it as being a human, Raghavachary said. If you painted the stop sign blue or changed a letter or flipped it, the self-driving car couldn't recognize it. "There are too many exceptions," Raghavachary said. He said that it's also the reason why Google's self-driving car is not mature enough yet to have widespread application. Here are some of the examples when the computer can't recognize the faces: "But humans have no problem recognizing it." However, a computer can't recognize a face in a photo if you change it - if you paint on the picture, or flip it or change the color to black and white - until it was trained, Raghavachary said.
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He said that in the case of the Chinese TV show "Super Brain," the robot seemed to surpass the human in facial recognition. Saty Raghavachary, a senior lecturer in the Computer Science Department at USC who teaches graphics and animation courses, seconded Biederman's perspective. But your computer can't tell until it's trained to see particular scenes like that." "It actually is a mechanical brain." Of the second image, he said, "even though you never saw it before, in a fraction of a second you realize that it's a medieval town. "You could make sense of it, right?" he said of the first image. "Artificial neural networks have been modeled of biological neural networks, but we don't have models of the whole brain because there's a lot more complexity." However, computers are not as good as humans in their perception and action, Biederman said.
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People have trouble recognizing many faces, he said, "because we have limited memory." "Computers do it in a very different way than people might be doing it," he said. Neuroscientist Irving Biederman, a professor of psychology and computer science at USC, is an expert on humans' ability to recognize and interpret what they see.