Customizing state-of-the-art deep learning models for new computer vision solutions
"Dramatic progress has been made in computer vision: deep neural networks (DNNs) trained on tens of millions of images can now recognize thousands of different object types. These DNNs can also be easily customized to new use cases. Timothy Hazen shares simple methods and tools that enable you...
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| Format: | eBook |
| Language: | English |
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[Place of publication not identified]
O'Reilly
2017
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| Collection: | O'Reilly - Collection details see MPG.ReNa |
| Summary: | "Dramatic progress has been made in computer vision: deep neural networks (DNNs) trained on tens of millions of images can now recognize thousands of different object types. These DNNs can also be easily customized to new use cases. Timothy Hazen shares simple methods and tools that enable you to adapt Microsoft's state-of-the-art DNNs for use in your own computer vision solutions."--Resource description page A presentation from the June 2017 O'Reilly Artificial Intelligence Conference in New York |
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| Item Description: | Title from title screen (viewed July 16, 2018) |
| Physical Description: | 1 streaming video file (37 min., 23 sec.) |