de Mauro et al., 2003 - Google Patents
Similarity learning for graph-based image representationsde Mauro et al., 2003
View PDF- Document ID
- 16988359661520729036
- Author
- de Mauro C
- Diligenti M
- Gori M
- Maggini M
- Publication year
- Publication venue
- Pattern Recognition Letters
External Links
Snippet
Visual database engines are usually based on predefined criteria for retrieving the images in response to a given query. In this paper, we propose a novel approach based on neural networks by which the retrieval criterion is derived on the basis of learning from examples. In …
- 230000001537 neural 0 abstract description 31
Classifications
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- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- 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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- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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- G06F17/3071—Clustering or classification including class or cluster creation or modification
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- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6251—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on a criterion of topology preservation, e.g. multidimensional scaling, self-organising maps
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