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Multi-View Graph Fusion for Semi-Supervised Learning: Application to Image-Based Face Beauty Prediction
dc.contributor.author | Dornaika, Fadi | |
dc.contributor.author | Moujahid, Abdelmalik | |
dc.date.accessioned | 2022-08-02T08:00:30Z | |
dc.date.available | 2022-08-02T08:00:30Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Algorithms 15(6) : (2022) // Article ID 207 | es_ES |
dc.identifier.issn | 1999-4893 | |
dc.identifier.uri | http://hdl.handle.net/10810/57127 | |
dc.description.abstract | Facial Beauty Prediction (FBP) is an important visual recognition problem to evaluate the attractiveness of faces according to human perception. Most existing FBP methods are based on supervised solutions using geometric or deep features. Semi-supervised learning for FBP is an almost unexplored research area. In this work, we propose a graph-based semi-supervised method in which multiple graphs are constructed to find the appropriate graph representation of the face images (with and without scores). The proposed method combines both geometric and deep feature-based graphs to produce a high-level representation of face images instead of using a single face descriptor and also improves the discriminative ability of graph-based score propagation methods. In addition to the data graph, our proposed approach fuses an additional graph adaptively built on the predicted beauty values. Experimental results on the SCUTFBP-5500 facial beauty dataset demonstrate the superiority of the proposed algorithm compared to other state-of-the-art methods. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | face beauty prediction | es_ES |
dc.subject | graph-based semi-supervised learning | es_ES |
dc.subject | graph fusion | es_ES |
dc.subject | score propagation | es_ES |
dc.subject | label graph | es_ES |
dc.subject | flexible manifold embedding | es_ES |
dc.title | Multi-View Graph Fusion for Semi-Supervised Learning: Application to Image-Based Face Beauty Prediction | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2022-06-23T12:20:49Z | |
dc.rights.holder | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/1999-4893/15/6/207 | es_ES |
dc.identifier.doi | 10.3390/a15060207 | |
dc.departamentoes | Ciencia de la computación e inteligencia artificial | |
dc.departamentoeu | Konputazio zientziak eta adimen artifiziala |
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This article is an open access article
distributed under the terms and
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4.0/).