Matches in SemOpenAlex for { <https://semopenalex.org/work/W2049243721> ?p ?o ?g. }
Showing items 1 to 99 of
99
with 100 items per page.
- W2049243721 abstract "We present Mi-Winnow, a new multiple-instance learning (MIL) algorithm that provides a new technique to convert MIL data into standard supervised data. In MIL each example is a collection (or bag) of d-dimensional points where each dimension corresponds to a feature. A label is provided for the bag, but not for the individual points within the bag. Mi-Winnow is different from existing multiple-instance learning algorithms in several key ways. First, Mi-Winnow allows each image to be converted into a bag in multiple ways to create training (and test) data that varies in both the number of dimensions per point, and in the kind of features used. Second, instead of learning a concept defined by a single point-and-scaling hypothesis, Mi-Winnow allows the underlying concept to be described by combining a set of separators learned by Winnow. For content-based image retrieval applications, such a generalized hypothesis is important since there may be different ways to recognize which images are of interest" @default.
- W2049243721 created "2016-06-24" @default.
- W2049243721 creator A5001987603 @default.
- W2049243721 creator A5017218993 @default.
- W2049243721 creator A5047205054 @default.
- W2049243721 date "2006-11-01" @default.
- W2049243721 modified "2023-09-25" @default.
- W2049243721 title "MI-Winnow: A New Multiple-Instance Learning Algorithm" @default.
- W2049243721 cites W1524926518 @default.
- W2049243721 cites W1540386283 @default.
- W2049243721 cites W1554039773 @default.
- W2049243721 cites W1560331282 @default.
- W2049243721 cites W1966848801 @default.
- W2049243721 cites W2023677852 @default.
- W2049243721 cites W2031979166 @default.
- W2049243721 cites W2040870580 @default.
- W2049243721 cites W2046434485 @default.
- W2049243721 cites W2049633694 @default.
- W2049243721 cites W2085261163 @default.
- W2049243721 cites W2087614174 @default.
- W2049243721 cites W2110119381 @default.
- W2049243721 cites W2113169966 @default.
- W2049243721 cites W2124410428 @default.
- W2049243721 cites W2129113961 @default.
- W2049243721 cites W2136595724 @default.
- W2049243721 cites W2150691697 @default.
- W2049243721 cites W2152195571 @default.
- W2049243721 cites W2154318594 @default.
- W2049243721 cites W2157825442 @default.
- W2049243721 cites W2163474322 @default.
- W2049243721 cites W334023122 @default.
- W2049243721 doi "https://doi.org/10.1109/ictai.2006.82" @default.
- W2049243721 hasPublicationYear "2006" @default.
- W2049243721 type Work @default.
- W2049243721 sameAs 2049243721 @default.
- W2049243721 citedByCount "4" @default.
- W2049243721 crossrefType "proceedings-article" @default.
- W2049243721 hasAuthorship W2049243721A5001987603 @default.
- W2049243721 hasAuthorship W2049243721A5017218993 @default.
- W2049243721 hasAuthorship W2049243721A5047205054 @default.
- W2049243721 hasConcept C11413529 @default.
- W2049243721 hasConcept C115961682 @default.
- W2049243721 hasConcept C119857082 @default.
- W2049243721 hasConcept C126422989 @default.
- W2049243721 hasConcept C138885662 @default.
- W2049243721 hasConcept C153180895 @default.
- W2049243721 hasConcept C154945302 @default.
- W2049243721 hasConcept C177264268 @default.
- W2049243721 hasConcept C199360897 @default.
- W2049243721 hasConcept C202444582 @default.
- W2049243721 hasConcept C2524010 @default.
- W2049243721 hasConcept C26517878 @default.
- W2049243721 hasConcept C2776401178 @default.
- W2049243721 hasConcept C28719098 @default.
- W2049243721 hasConcept C33676613 @default.
- W2049243721 hasConcept C33923547 @default.
- W2049243721 hasConcept C38652104 @default.
- W2049243721 hasConcept C38785706 @default.
- W2049243721 hasConcept C41008148 @default.
- W2049243721 hasConcept C41895202 @default.
- W2049243721 hasConcept C9417928 @default.
- W2049243721 hasConceptScore W2049243721C11413529 @default.
- W2049243721 hasConceptScore W2049243721C115961682 @default.
- W2049243721 hasConceptScore W2049243721C119857082 @default.
- W2049243721 hasConceptScore W2049243721C126422989 @default.
- W2049243721 hasConceptScore W2049243721C138885662 @default.
- W2049243721 hasConceptScore W2049243721C153180895 @default.
- W2049243721 hasConceptScore W2049243721C154945302 @default.
- W2049243721 hasConceptScore W2049243721C177264268 @default.
- W2049243721 hasConceptScore W2049243721C199360897 @default.
- W2049243721 hasConceptScore W2049243721C202444582 @default.
- W2049243721 hasConceptScore W2049243721C2524010 @default.
- W2049243721 hasConceptScore W2049243721C26517878 @default.
- W2049243721 hasConceptScore W2049243721C2776401178 @default.
- W2049243721 hasConceptScore W2049243721C28719098 @default.
- W2049243721 hasConceptScore W2049243721C33676613 @default.
- W2049243721 hasConceptScore W2049243721C33923547 @default.
- W2049243721 hasConceptScore W2049243721C38652104 @default.
- W2049243721 hasConceptScore W2049243721C38785706 @default.
- W2049243721 hasConceptScore W2049243721C41008148 @default.
- W2049243721 hasConceptScore W2049243721C41895202 @default.
- W2049243721 hasConceptScore W2049243721C9417928 @default.
- W2049243721 hasLocation W20492437211 @default.
- W2049243721 hasOpenAccess W2049243721 @default.
- W2049243721 hasPrimaryLocation W20492437211 @default.
- W2049243721 hasRelatedWork W2003465964 @default.
- W2049243721 hasRelatedWork W2057623054 @default.
- W2049243721 hasRelatedWork W2317200988 @default.
- W2049243721 hasRelatedWork W2371447506 @default.
- W2049243721 hasRelatedWork W2376932109 @default.
- W2049243721 hasRelatedWork W2386767533 @default.
- W2049243721 hasRelatedWork W2748952813 @default.
- W2049243721 hasRelatedWork W2899084033 @default.
- W2049243721 hasRelatedWork W3107474891 @default.
- W2049243721 hasRelatedWork W4225307033 @default.
- W2049243721 isParatext "false" @default.
- W2049243721 isRetracted "false" @default.
- W2049243721 magId "2049243721" @default.
- W2049243721 workType "article" @default.