Matches in SemOpenAlex for { <https://semopenalex.org/work/W91070968> ?p ?o ?g. }
Showing items 1 to 89 of
89
with 100 items per page.
- W91070968 endingPage "198" @default.
- W91070968 startingPage "181" @default.
- W91070968 abstract "Self-organising neural networks have shown promise in a variety of applications areas. Their massive and intrinsic parallelism makes those networks suitable to solve hard problems in image-analysis and computer vision applications, especially when non-stationary environments occur. Moreover, this kind of neural networks preserves the topology of an input space by using their inherited competitive learning property. In this work we use a kind of self-organising network, the Growing Neural Gas, to solve some computer vision tasks applied to visual surveillance systems. The neural network is also modified to accelerate the learning algorithm in order to support applications with temporal constraints. This feature has been used to build a system able to track image features in video sequences. The system automatically keeps the correspondence of features among frames in the sequence using its own structure. Information obtained during the tracking process and allocated in the neural network can also be used to analyse the objects motion.KeywordsInput SpacePrevious FrameReference VectorHand Gesture RecognitionVisual SurveillanceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
- W91070968 created "2016-06-24" @default.
- W91070968 creator A5038077349 @default.
- W91070968 creator A5063682950 @default.
- W91070968 creator A5079599826 @default.
- W91070968 creator A5086573631 @default.
- W91070968 date "2012-01-01" @default.
- W91070968 modified "2023-09-23" @default.
- W91070968 title "Building Visual Surveillance Systems with Neural Networks" @default.
- W91070968 cites W1507785524 @default.
- W91070968 cites W1560851313 @default.
- W91070968 cites W1768921720 @default.
- W91070968 cites W1850475525 @default.
- W91070968 cites W1974277138 @default.
- W91070968 cites W1987517671 @default.
- W91070968 cites W2012031343 @default.
- W91070968 cites W2021057537 @default.
- W91070968 cites W2046440659 @default.
- W91070968 cites W2047870719 @default.
- W91070968 cites W2071509342 @default.
- W91070968 cites W2093691623 @default.
- W91070968 cites W2094084300 @default.
- W91070968 cites W2111818318 @default.
- W91070968 cites W2118572719 @default.
- W91070968 cites W2121224247 @default.
- W91070968 cites W2127893047 @default.
- W91070968 cites W2128534087 @default.
- W91070968 cites W2140235142 @default.
- W91070968 cites W2140745919 @default.
- W91070968 cites W4245176872 @default.
- W91070968 doi "https://doi.org/10.1007/978-3-642-25237-2_11" @default.
- W91070968 hasPublicationYear "2012" @default.
- W91070968 type Work @default.
- W91070968 sameAs 91070968 @default.
- W91070968 citedByCount "2" @default.
- W91070968 countsByYear W910709682015 @default.
- W91070968 countsByYear W910709682018 @default.
- W91070968 crossrefType "book-chapter" @default.
- W91070968 hasAuthorship W91070968A5038077349 @default.
- W91070968 hasAuthorship W91070968A5063682950 @default.
- W91070968 hasAuthorship W91070968A5079599826 @default.
- W91070968 hasAuthorship W91070968A5086573631 @default.
- W91070968 hasBestOaLocation W910709682 @default.
- W91070968 hasConcept C111472728 @default.
- W91070968 hasConcept C111919701 @default.
- W91070968 hasConcept C119857082 @default.
- W91070968 hasConcept C138885662 @default.
- W91070968 hasConcept C147168706 @default.
- W91070968 hasConcept C154945302 @default.
- W91070968 hasConcept C189950617 @default.
- W91070968 hasConcept C2776401178 @default.
- W91070968 hasConcept C31972630 @default.
- W91070968 hasConcept C41008148 @default.
- W91070968 hasConcept C41895202 @default.
- W91070968 hasConcept C50644808 @default.
- W91070968 hasConcept C98045186 @default.
- W91070968 hasConceptScore W91070968C111472728 @default.
- W91070968 hasConceptScore W91070968C111919701 @default.
- W91070968 hasConceptScore W91070968C119857082 @default.
- W91070968 hasConceptScore W91070968C138885662 @default.
- W91070968 hasConceptScore W91070968C147168706 @default.
- W91070968 hasConceptScore W91070968C154945302 @default.
- W91070968 hasConceptScore W91070968C189950617 @default.
- W91070968 hasConceptScore W91070968C2776401178 @default.
- W91070968 hasConceptScore W91070968C31972630 @default.
- W91070968 hasConceptScore W91070968C41008148 @default.
- W91070968 hasConceptScore W91070968C41895202 @default.
- W91070968 hasConceptScore W91070968C50644808 @default.
- W91070968 hasConceptScore W91070968C98045186 @default.
- W91070968 hasLocation W910709681 @default.
- W91070968 hasLocation W910709682 @default.
- W91070968 hasOpenAccess W91070968 @default.
- W91070968 hasPrimaryLocation W910709681 @default.
- W91070968 hasRelatedWork W1504288058 @default.
- W91070968 hasRelatedWork W2048505601 @default.
- W91070968 hasRelatedWork W2116675934 @default.
- W91070968 hasRelatedWork W2167293474 @default.
- W91070968 hasRelatedWork W2331674254 @default.
- W91070968 hasRelatedWork W2358403311 @default.
- W91070968 hasRelatedWork W2544359817 @default.
- W91070968 hasRelatedWork W3042897387 @default.
- W91070968 hasRelatedWork W4310007291 @default.
- W91070968 hasRelatedWork W2971052914 @default.
- W91070968 isParatext "false" @default.
- W91070968 isRetracted "false" @default.
- W91070968 magId "91070968" @default.
- W91070968 workType "book-chapter" @default.