EP3593284A4 - A transductive and/or adaptive max margin zero-shot learning method and system - Google Patents
A transductive and/or adaptive max margin zero-shot learning method and system Download PDFInfo
- Publication number
- EP3593284A4 EP3593284A4 EP17899880.3A EP17899880A EP3593284A4 EP 3593284 A4 EP3593284 A4 EP 3593284A4 EP 17899880 A EP17899880 A EP 17899880A EP 3593284 A4 EP3593284 A4 EP 3593284A4
- Authority
- EP
- European Patent Office
- Prior art keywords
- transductive
- learning method
- shot learning
- max margin
- adaptive max
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
- G06F18/2135—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on approximation criteria, e.g. principal component analysis
- G06F18/21355—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on approximation criteria, e.g. principal component analysis nonlinear criteria, e.g. embedding a manifold in a Euclidean space
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
- G06F18/2155—Generating training patterns; Bootstrap methods, e.g. bagging or boosting characterised by the incorporation of unlabelled data, e.g. multiple instance learning [MIL], semi-supervised techniques using expectation-maximisation [EM] or naïve labelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/50—Extraction of image or video features by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
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- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Engineering & Computer Science (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Software Systems (AREA)
- Multimedia (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Medical Informatics (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
PCT/CN2017/075764 WO2018161217A1 (en) | 2017-03-06 | 2017-03-06 | A transductive and/or adaptive max margin zero-shot learning method and system |
Publications (2)
Publication Number | Publication Date |
---|---|
EP3593284A1 EP3593284A1 (en) | 2020-01-15 |
EP3593284A4 true EP3593284A4 (en) | 2021-03-10 |
Family
ID=63447133
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP17899880.3A Pending EP3593284A4 (en) | 2017-03-06 | 2017-03-06 | A transductive and/or adaptive max margin zero-shot learning method and system |
Country Status (3)
Country | Link |
---|---|
EP (1) | EP3593284A4 (en) |
CN (1) | CN110431565B (en) |
WO (1) | WO2018161217A1 (en) |
Families Citing this family (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109598279B (en) * | 2018-09-27 | 2023-04-25 | 天津大学 | Zero sample learning method based on self-coding countermeasure generation network |
CN109582960B (en) * | 2018-11-27 | 2020-11-24 | 上海交通大学 | Zero example learning method based on structured association semantic embedding |
EP3751467A1 (en) * | 2019-06-14 | 2020-12-16 | Robert Bosch GmbH | A machine learning system |
CN113763744A (en) * | 2020-06-02 | 2021-12-07 | 荷兰移动驱动器公司 | Parking position reminding method and vehicle-mounted device |
CN111914872B (en) * | 2020-06-04 | 2024-02-02 | 西安理工大学 | Zero sample image classification method with label and semantic self-coding fused |
CN115424096B (en) * | 2022-11-08 | 2023-01-31 | 南京信息工程大学 | Multi-view zero-sample image identification method |
CN116051909B (en) * | 2023-03-06 | 2023-06-16 | 中国科学技术大学 | Direct push zero-order learning unseen picture classification method, device and medium |
CN117541882B (en) * | 2024-01-05 | 2024-04-19 | 南京信息工程大学 | Instance-based multi-view vision fusion transduction type zero sample classification method |
CN117893743B (en) * | 2024-03-18 | 2024-05-31 | 山东军地信息技术集团有限公司 | Zero sample target detection method based on channel weighting and double-comparison learning |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20160253597A1 (en) * | 2015-02-27 | 2016-09-01 | Xerox Corporation | Content-aware domain adaptation for cross-domain classification |
Family Cites Families (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101179860B (en) * | 2007-12-05 | 2011-03-16 | 中兴通讯股份有限公司 | ZC sequence ranking method and apparatus for random access channel |
US10331976B2 (en) * | 2013-06-21 | 2019-06-25 | Xerox Corporation | Label-embedding view of attribute-based recognition |
WO2016145379A1 (en) * | 2015-03-12 | 2016-09-15 | William Marsh Rice University | Automated Compilation of Probabilistic Task Description into Executable Neural Network Specification |
CN105512679A (en) * | 2015-12-02 | 2016-04-20 | 天津大学 | Zero sample classification method based on extreme learning machine |
CN105701504B (en) * | 2016-01-08 | 2019-09-13 | 天津大学 | Multi-modal manifold embedding grammar for zero sample learning |
CN105701514B (en) * | 2016-01-15 | 2019-05-21 | 天津大学 | A method of the multi-modal canonical correlation analysis for zero sample classification |
CN105718940B (en) * | 2016-01-15 | 2019-03-29 | 天津大学 | The zero sample image classification method based on factorial analysis between multiple groups |
CN105740888A (en) * | 2016-01-26 | 2016-07-06 | 天津大学 | Joint embedded model for zero sample learning |
CN106096661B (en) * | 2016-06-24 | 2019-03-01 | 中国科学院电子学研究所苏州研究院 | The zero sample image classification method based on relative priority random forest |
CN106203472B (en) * | 2016-06-27 | 2019-04-02 | 中国矿业大学 | A kind of zero sample image classification method based on the direct prediction model of mixed attributes |
CN106203483B (en) * | 2016-06-29 | 2019-06-11 | 天津大学 | A kind of zero sample image classification method based on semantic related multi-modal mapping method |
CN106250925B (en) * | 2016-07-25 | 2019-06-11 | 天津大学 | A kind of zero Sample video classification method based on improved canonical correlation analysis |
-
2017
- 2017-03-06 CN CN201780088157.6A patent/CN110431565B/en active Active
- 2017-03-06 EP EP17899880.3A patent/EP3593284A4/en active Pending
- 2017-03-06 WO PCT/CN2017/075764 patent/WO2018161217A1/en unknown
Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20160253597A1 (en) * | 2015-02-27 | 2016-09-01 | Xerox Corporation | Content-aware domain adaptation for cross-domain classification |
Also Published As
Publication number | Publication date |
---|---|
CN110431565B (en) | 2023-06-20 |
CN110431565A (en) | 2019-11-08 |
EP3593284A1 (en) | 2020-01-15 |
WO2018161217A1 (en) | 2018-09-13 |
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RIC1 | Information provided on ipc code assigned before grant |
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