FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2162746294> ?p ?o ?g. }

• W2162746294 endingPage "49" @default.
• W2162746294 startingPage "2132" @default.
• W2162746294 abstract "Wavelet neural networks combine the functions of time-frequency localization from the wavelet transform and of self-studying from the neural network, which make them particularly suitable for the classification of complex patterns. In this paper, an efficient object recognition method using boundary representation and the wavelet neural network is proposed. The method employs a wavelet neural network (WNN) to characterize the singularities of the object curvature representation and to perform the object classification at the same time and in an automatic way. The local time-frequency attributes of the singularities on the object boundary are detected by making a preliminary wavelet analysis of the curvature representation. Then, the discriminative scale-translation features of the singularities are stored as the initial scale-translation parameters of the wavelet nodes in the WNN. These parameters are trained to their optimum status during the learning stage. With our approach, as opposed to matching features by convolving the signal with wavelet functions at a large number of scales, the computational burden is significantly reduced. Only a few convolutions are performed at the optimum scale-translation grids during the classification, which makes it suitable for real-time recognition tasks. Compared with the artificial-neural-network-based approaches preceded by wavelet filter banks with fixed scale-translation parameters, the support vector machine (SVM) using traditional Fourier descriptors and K-nearest-neighbor ( K-NN) classifier based on the state-of-the-art shape descriptors, our scheme demonstrates superior and stable discrimination performance under various noisy and affine conditions." @default.
• W2162746294 created "2016-06-24" @default.
• W2162746294 creator A5003165832 @default.
• W2162746294 creator A5083939413 @default.
• W2162746294 date "2008-12-01" @default.
• W2162746294 modified "2023-10-16" @default.
• W2162746294 title "Efficient object recognition using boundary representation and wavelet neural network." @default.
• W2162746294 cites W109390732 @default.
• W2162746294 cites W1504736116 @default.
• W2162746294 cites W1925362108 @default.
• W2162746294 cites W1963812344 @default.
• W2162746294 cites W1966236750 @default.
• W2162746294 cites W1970876195 @default.
• W2162746294 cites W1973040917 @default.
• W2162746294 cites W1988116054 @default.
• W2162746294 cites W1998628605 @default.
• W2162746294 cites W2002126584 @default.
• W2162746294 cites W2018783332 @default.
• W2162746294 cites W2019819286 @default.
• W2162746294 cites W2025616541 @default.
• W2162746294 cites W2034396562 @default.
• W2162746294 cites W2039845656 @default.
• W2162746294 cites W2046650367 @default.
• W2162746294 cites W2052277674 @default.
• W2162746294 cites W2053695442 @default.
• W2162746294 cites W2057175746 @default.
• W2162746294 cites W2072738093 @default.
• W2162746294 cites W2077776908 @default.
• W2162746294 cites W2080495424 @default.
• W2162746294 cites W2082346459 @default.
• W2162746294 cites W2085806937 @default.
• W2162746294 cites W2098386213 @default.
• W2162746294 cites W2100689562 @default.
• W2162746294 cites W2103052024 @default.
• W2162746294 cites W2105542305 @default.
• W2162746294 cites W2105693855 @default.
• W2162746294 cites W2108556791 @default.
• W2162746294 cites W2112547574 @default.
• W2162746294 cites W2115790233 @default.
• W2162746294 cites W2117336628 @default.
• W2162746294 cites W2122827492 @default.
• W2162746294 cites W2122986041 @default.
• W2162746294 cites W2145023731 @default.
• W2162746294 cites W2147789761 @default.
• W2162746294 cites W2152328854 @default.
• W2162746294 cites W2154332114 @default.
• W2162746294 cites W2156798906 @default.
• W2162746294 cites W2156909104 @default.
• W2162746294 cites W2157007857 @default.
• W2162746294 cites W2157164240 @default.
• W2162746294 cites W2159498975 @default.
• W2162746294 cites W2171357473 @default.
• W2162746294 cites W2171506994 @default.
• W2162746294 cites W2293747114 @default.
• W2162746294 cites W4214540058 @default.
• W2162746294 cites W4239510810 @default.
• W2162746294 cites W2076567023 @default.
• W2162746294 doi "https://doi.org/10.1109/tnn.2008.2006331" @default.
• W2162746294 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/19054736" @default.
• W2162746294 hasPublicationYear "2008" @default.
• W2162746294 type Work @default.
• W2162746294 sameAs 2162746294 @default.
• W2162746294 citedByCount "51" @default.
• W2162746294 countsByYear W21627462942012 @default.
• W2162746294 countsByYear W21627462942013 @default.
• W2162746294 countsByYear W21627462942014 @default.
• W2162746294 countsByYear W21627462942015 @default.
• W2162746294 countsByYear W21627462942016 @default.
• W2162746294 countsByYear W21627462942017 @default.
• W2162746294 countsByYear W21627462942018 @default.
• W2162746294 countsByYear W21627462942019 @default.
• W2162746294 countsByYear W21627462942020 @default.
• W2162746294 countsByYear W21627462942021 @default.
• W2162746294 countsByYear W21627462942022 @default.
• W2162746294 crossrefType "journal-article" @default.
• W2162746294 hasAuthorship W2162746294A5003165832 @default.
• W2162746294 hasAuthorship W2162746294A5083939413 @default.
• W2162746294 hasConcept C153180895 @default.
• W2162746294 hasConcept C154945302 @default.
• W2162746294 hasConcept C155777637 @default.
• W2162746294 hasConcept C196216189 @default.
• W2162746294 hasConcept C33923547 @default.
• W2162746294 hasConcept C41008148 @default.
• W2162746294 hasConcept C47432892 @default.
• W2162746294 hasConcept C50644808 @default.
• W2162746294 hasConcept C88829872 @default.
• W2162746294 hasConcept C97931131 @default.
• W2162746294 hasConceptScore W2162746294C153180895 @default.
• W2162746294 hasConceptScore W2162746294C154945302 @default.
• W2162746294 hasConceptScore W2162746294C155777637 @default.
• W2162746294 hasConceptScore W2162746294C196216189 @default.
• W2162746294 hasConceptScore W2162746294C33923547 @default.
• W2162746294 hasConceptScore W2162746294C41008148 @default.
• W2162746294 hasConceptScore W2162746294C47432892 @default.
• W2162746294 hasConceptScore W2162746294C50644808 @default.
• W2162746294 hasConceptScore W2162746294C88829872 @default.
• W2162746294 hasConceptScore W2162746294C97931131 @default.
• W2162746294 hasIssue "12" @default.

• next