New framework improves performance of deep neural networks

North Carolina State University researchers have developed a new framework for building deep neural networks via grammar-guided network generators. In experimental testing, the new networks—called AOGNets—have outperformed existing state-of-the-art frameworks, including the widely-used ResNet and DenseNet systems, in visual recognition tasks.

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Want to eliminate workplace bias? Watch your rating system, study says

What's the difference between a 10-point and a six-point performance rating scale, besides four points?

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A social perception scheme for behavior planning of autonomous cars

To navigate dynamic environments, autonomous vehicles (AVs) should be able to process all information available to them and use it to generate effective driving strategies. Researchers at the University of California, Berkeley, have recently proposed a social perception scheme for planning the behavior of autonomous cars, which could help to develop AVs that are better equipped to deal with uncertainty in their surrounding environment.

* This article was originally published here