Conference item
Interpolating convolutional neural networks using batch normalization
- Abstract:
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Perceiving a visual concept as a mixture of learned ones is natural for humans, aiding them to grasp new concepts and strengthening old ones. For all their power and recent success, deep convolutional networks do not have this ability. Inspired by recent work on universal representations for neural networks, we propose a simple emulation of this mechanism by purposing batch normalization layers to discriminate visual classes, and formulating a way to combine them to solve new tasks. We show t...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
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(Accepted manuscript, pdf, 539.3KB)
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- Publisher copy:
- 10.1007/978-3-030-01261-8_35
Authors
Bibliographic Details
- Publisher:
- Springer Publisher's website
- Journal:
- 15th European Conference on Computer Vision (ECCV 2018) Journal website
- Host title:
- 15th European Conference on Computer Vision (ECCV 2018)
- Publication date:
- 2018-10-06
- Acceptance date:
- 2018-07-03
- DOI:
- ISSN:
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1611-3349 and 0302-9743
- Source identifiers:
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938457
- ISBN:
- 9783030012601
Item Description
- Keywords:
- Pubs id:
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pubs:938457
- UUID:
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uuid:3be8efd8-cb06-458e-9f4b-62dd2d0693a9
- Local pid:
- pubs:938457
- Deposit date:
- 2018-11-08
Terms of use
- Copyright holder:
- Springer Nature Switzerland AG
- Copyright date:
- 2018
- Notes:
- © Springer Nature Switzerland AG 2018. This is the accepted manuscript version of the article. The final version is available online from Springer at: https://doi.org/10.1007/978-3-030-01261-8_35
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