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Microsoft, Google one-up humans in image recognition

Posted: 20 Feb 2015     Print Version  Bookmark and Share

Keywords:image recognition  deep learning algorithm  neural network 

"A robust initialisation method, as a part of training algorithm, was needed since training very deep neural networks is difficult. Previous work either resorts to pre-training or adding auxiliary training tasks. In our work, we derive a theoretically sound initialisation method, which allows us to freely exploit more powerful—deeper and wider—neural networks," Sun told EE Times.

Nvidia Corp. is a sponsor of the annual ImageNet Challenge and supplies access to arrays of its graphic processing units (GPUs) to all contestants. Microsoft did use Nvidia GPUs but bought and configured their own supercomputer using them to simulate parametric rectified linear neural units to become the "first to beat a human" at image classification.

The team's results are already being applied to Microsoft's Bing image search and OneDrive. Sun's team consisted of Kaiming He, at Microsoft Research Asia's Visual Computing Group, and two academic interns, Xiangyu Zhang of Xi'an Jiaotong University and Shaoqing Ren of the University of Science and Technology of China.

- R. Colin Johnson
  EE Times

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