Yang et al., 2019 - Google Patents
Zero-shot transfer learning based on visual and textual resemblanceYang et al., 2019
- Document ID
- 8187666174886714228
- Author
- Yang G
- Xu J
- Publication year
- Publication venue
- International Conference on Neural Information Processing
External Links
Snippet
Existing image search engines, whose ranking functions are built based on labeled images or wrap texts, have poor results on queries in new, or low-frequency keywords. In this paper, we put forward the zero-shot transfer learning (ZSTL), which aims to transfer networks from …
- 230000000007 visual effect 0 title abstract description 43
Classifications
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- G06—COMPUTING; CALCULATING; COUNTING
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- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30861—Retrieval from the Internet, e.g. browsers
- G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
- G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
- G06F17/30247—Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image data
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- G06F17/30731—Creation of semantic tools
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- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
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