Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...
A joint research team has developed a deep neural network named DeepTFactor that predicts transcription factors from protein sequences. DeepTFactor will serve as a useful tool for understanding the ...
A study shows that a deep neural network model can accurately predict the brain age of healthy patients based on electroencephalogram data recorded during an overnight sleep study, and EEG-predicted ...
Deep neural networks have gained fame for their capability to process visual information. And in the past few years, they have become a key component of many computer vision applications. Among the ...
Deep neural networks can perform wonderful feats, thanks to their extremely large and complicated web of parameters. But their complexity is also their curse: The inner workings of neural networks are ...
In the winter of 2011, Daniel Yamins, a postdoctoral researcher in computational neuroscience at the Massachusetts Institute of Technology, would at times toil past midnight on his machine vision ...
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Enhanced phase-shifting technique captures 3D shapes of moving objects with high precision
Researchers at the Institute of Science Tokyo have developed a neural-network-based 3D imaging technique that can precisely ...
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