| 000 | 02763nam a22003975i 4500 | ||
|---|---|---|---|
| 999 |
_c103579 _d103579 _x1 |
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| 001 | 103579 | ||
| 003 | DE-He213 | ||
| 005 | 20230102113137.0 | ||
| 006 | a||||fo|||| 00| 0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 150509s2015 si | s |||| 0|eng d | ||
| 020 | _a9789812874689 | ||
| 024 | 7 |
_a10.1007/978-981-287-468-9 _2doi |
|
| 040 |
_bspa _dES-MaUEC |
||
| 050 | 4 |
_aQ325.5 _bX856 2015 EB |
|
| 100 | 1 |
_aXu, Long. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _0http://id.loc.gov/authorities/names/nr88012057 _1http://viaf.org/viaf/25402840/ |
|
| 245 | 1 | 0 |
_aVisual Quality Assessment by Machine Learning _cby Long Xu, Weisi Lin, C.-C. Jay Kuo. |
| 264 | 1 |
_aSingapore _bSpringer International Publishing _c2015 |
|
| 300 | _a1 recurso en línea (XIV, 132 páginas 19 ilustraciones, 16 ilustraciones a color.) | ||
| 336 |
_2rdacontent _aTexto (visual) _btxt |
||
| 337 |
_2rdamedia _aelectrónico _bc |
||
| 338 |
_2rdacarrier _arecurso electrónico _bcr |
||
| 490 | 0 |
_aSpringerBriefs in Signal Processing, _x2196-4076 |
|
| 490 | 0 | _aEngineering (Springer-11647) | |
| 505 | 0 | _aIntroduction -- Fundamental knowledges of machine learning -- Image features and feature processing -- Feature pooling by learning -- Metrics fusion -- Summary and remarks for future research. | |
| 520 | 3 | _aThe book encompasses the state-of-the-art visual quality assessment (VQA) and learning based visual quality assessment (LB-VQA) by providing a comprehensive overview of the existing relevant methods. It delivers the readers the basic knowledge, systematic overview and new development of VQA. It also encompasses the preliminary knowledge of Machine Learning (ML) to VQA tasks and newly developed ML techniques for the purpose. Hence, firstly, it is particularly helpful to the beginner-readers (including research students) to enter into VQA field in general and LB-VQA one in particular. Secondly, new development in VQA and LB-VQA particularly are detailed in this book, which will give peer researchers and engineers new insights in VQA. | |
| 988 | _aEBSPRINGER_2018 | ||
| 650 | 7 |
_aAprendizaje automático _2embne _9166090 |
|
| 700 | 1 |
_aLin, Weisi. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _0http://id.loc.gov/authorities/names/no2011192230 _1http://viaf.org/viaf/24599625/ |
|
| 700 | 1 |
_aKuo, C.-C. Jay. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/8998466/ _9100843 |
|
| 776 | 0 | 8 |
_iEdición impresa: _z9789812874696 |
| 776 | 0 | 8 |
_iEdición impresa: _z9789812874672 |
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-287-468-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 942 |
_2lcc _cLE |
||
| 998 |
_b03/2019 _dz _eIG _zSI |
||