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We live in a world increasingly dependent on the Internet for information retrieval, social interaction and general leisure. A growing number of Internet users with cognitive or visual impairments need assistive technology to make information accessible to them, but visually complex web pages can be difficult to navigate for assistive technology.

When an election is held we often employ a peculiar kind of logic. As we mull over the candidates we may have a top choice, but if we think our preferred candidate isn’t going to win we might vote for our second choice. Or maybe we cast a ballot for our second choice because we want to make sure that a frontrunner who doesn’t represent our view loses.

Professor Jeff Orchard and third-year undergraduate computer science student Louis Castricato received a best paper award at the 24th International Conference on Neural Informational Processing (ICONIP 2017) for their paper titled “Combating adversarial inputs using a predictive-estimator network.”

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