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• W2892353009 abstract "Manifold embedding techniques have properties that render them attractive candidates to learn a compact and general representation of a three dimensional spatial object. In turn this representation can be used for object recognition through classification. This paper presents a comparative study of several supervised spectral embedding techniques and their relationship with the feature space used to describe the exemplars which act as inputs to an embedding procedure. By concentrating on this aspect, we are able to highlight preferential combinations between feature description and embedding, and we formulate recommendations on the use of such methods for fusing multiple views of an object to recognize it under variable poses." @default.
• W2892353009 created "2018-09-27" @default.
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• W2892353009 date "2018-07-01" @default.
• W2892353009 modified "2023-09-25" @default.
• W2892353009 title "Comparing Interrelationships Between Features and Embedding Methods for Multiple-View Fusion" @default.
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• W2892353009 doi "https://doi.org/10.23919/icif.2018.8455547" @default.
• W2892353009 hasPublicationYear "2018" @default.
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