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Customizing state-of-the-art deep learning models for new computer vision solutions / Hazen, Timothy.
- Format:
- Video
- Author/Creator:
- Hazen, Timothy, author.
- Buehler, Patrick, author.
- Carapcea, Cornelia, author.
- Roth, Anna, author.
- Language:
- English
- Subjects (All):
- Machine learning.
- Artificial intelligence.
- Neural networks (Computer science).
- Computer software.
- O'Reilly Artificial Intelligence Conference (2017 : New York, New York).
- O'Reilly Artificial Intelligence Conference.
- Genre:
- Electronic videos.
- Physical Description:
- 1 online resource (1 video file, approximately 37 min.)
- Edition:
- 1st edition
- Place of Publication:
- O'Reilly Media, Inc., 2018.
- System Details:
- video file
- 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.
- Participant:
- Presenter, Timothy Hazen.
- Notes:
- Online resource; Title from title screen (viewed June 26, 2018)
- Title from title screen (viewed July 16, 2018).
- OCLC:
- 1044741320
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