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008			200528s2020 gw a o |||| 0|eng d
020			_a9783030392123
024	7		_a10.1007/978-3-030-39212-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQK569.D54 _b2020 EB
245	0	0	_aModern Trends in Diatom Identification : _bFundamentals and Applications _cedited by Gabriel Cristóbal, Saúl Blanco, Gloria Bueno
250			_aFirst edition
264		1	_aCham, Switzerland _bSpringer International Publishing _c2020
300			_a1 recurso en línea (XXIV, 294 páginas) _b239 ilustraciones, 166 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
490	0		_aDevelopments in Applied Phycology ; _v10
490	0		_aBiomedical and Life Sciences (Springer-11642)
505	0		_aPart 1: Fundamentals -- Chapter 1: Introduction -- Chapter 2: Diatom Classifications: What Purpose Do They Serve? -- Chapter 3: Diatom Taxonomy And Identification Keys -- Chapter 4: Teratologies/Life Cycle/Ecotoxicology -- Part 2: Sensing -- Chapter 5: Microscope Lighting Techniques -- Chapter 6: Microscope Filtering Techniques -- Chapter 7: Automatization Techniques. Slide Scanning -- Part 3: Analysis -- Chapter 8: Segmentation -- Chapter 9: Feature Extraction And Classification -- Chapter 10: Multifocus And Hdr -- Chapter 11: 3d Imaging -- Chapter 12: Morphometrics -- Part 4: Applications -- Chapter 13: Water Quality Assessment -- Chapter 14: Diatoms In Forensic Analysis -- Chapter 15: Benthic Foraminifera And Diatoms As Ecological Indicators.
520	3		_aHigh-resolution images of phytoplankton cells such as diatoms or desmids, which are useful for monitoring water quality, can now be provided by digital microscopes, facilitating the automated analysis and identification of specimens. Conventional approaches are based on optical microscopy; however, manual image analysis is impractical due to the huge diversity of this group of microalgae and its great morphological plasticity. As such, there is a need for automated recognition techniques for diagnostic tools (e.g. environmental monitoring networks, early warning systems) to improve the management of water resources and decision-making processes. Describing the entire workflow of a bioindicator system, from capture, analysis and identification to the determination of quality indices, this book provides insights into the current state-of-the-art in automatic identification systems in microscopy. .
988			_aSpringer_Biomedlife_23062020
650		7	_aDiatomeas _2embne _9675041
700	1		_aCristóbal, Gabriel _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/no2007011411 _1http://viaf.org/viaf/170087218
700	1		_aBlanco, Saúl _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt _1http://viaf.org/viaf/313528606
700	1		_aBueno, Gloria _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/no2019120516 _1http://viaf.org/viaf/19156674885933580429
710	2		_aSpringerLink (Online service) _0http://id.loc.gov/authorities/names/no2005046756 _1http://viaf.org/viaf/148105729
776	0	8	_iPrinted edition: _z9783030392116
776	0	8	_iPrinted edition: _z9783030392130
776	0	8	_iPrinted edition: _z9783030392147
830		0	_aDevelopments in Applied Phycology ; _v10
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-39212-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b07/2020 _dz _eo _zSI