Holdings: Scale space and variational methods in computer vision

Scale space and variational methods in computer vision: 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019 : proceedings

Saved in:

Bibliographic Details
Corporate Author:	SSVM Hofgeismar (Author)
Other Authors:	Lellmann, Jan (Editor), Burger, Martin (Editor), Modersitzki, Jan (Editor)
Format:	Electronic Conference Proceeding eBook
Language:	English
Published:	Cham Springer [2019]
Series:	Lecture notes in computer science 11603 : Image processing, computer vision, pattern recognition, and graphics
Subjects:	Image Processing and Computer Vision Numeric Computing Math Applications in Computer Science Artificial Intelligence Computer vision Electronic data processing Computer science Artificial intelligence Geometrieverarbeitung Rauschunterdrückung Merkmalsextraktion Level-Set-Methode Bildverarbeitung Variationsrechnung Skalenraum Maschinelles Sehen Konferenzschrift > 2019 > Hofgeismar
Online Access:	DE-634 DE-Aug4 DE-573 DE-M347 DE-92 DE-898 DE-859 DE-860 DE-861 DE-863 DE-862 DE-523 DE-91 DE-473 DE-19 DE-355 DE-703 DE-20 DE-706 DE-29 DE-739 Volltext
Physical Description:	1 Online-Ressource (xvii, 574 Seiten) Illustrationen, Diagramme
ISBN:	9783030223687
DOI:	10.1007/978-3-030-22368-7

Staff View

MARC


LEADER	00000nam a2200000zcb4500
001	BV046062464
003	DE-604
005	20250318
007	cr\|uuu---uuuuu
008	190724s2019 xx a\|\|\| o\|\|\|\| 10\|\|\| eng d
020			\|a 9783030223687 \|c Online \|9 978-3-030-22368-7
024	7		\|a 10.1007/978-3-030-22368-7 \|2 doi
035			\|a (ZDB-2-SCS)9783030223687
035			\|a (ZDB-2-LNC)9783030223687
035			\|a (OCoLC)1111824445
035			\|a (DE-599)BVBBV046062464
040			\|a DE-604 \|b ger \|e rda
041	0		\|a eng
049			\|a DE-355 \|a DE-860 \|a DE-91 \|a DE-19 \|a DE-Aug4 \|a DE-898 \|a DE-861 \|a DE-523 \|a DE-859 \|a DE-473 \|a DE-29 \|a DE-863 \|a DE-20 \|a DE-862 \|a DE-92 \|a DE-573 \|a DE-M347 \|a DE-703 \|a DE-706 \|a DE-739 \|a DE-634
082	0		\|a 006.37 \|2 23
082	0		\|a 006.6 \|2 23
084			\|a DAT 760f \|2 stub
084			\|a DAT 000 \|2 stub
111	2		\|a SSVM \|n 7. \|d 2019 \|c Hofgeismar \|j Verfasser \|0 (DE-588)118865389X \|4 aut
245	1	0	\|a Scale space and variational methods in computer vision \|b 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019 : proceedings \|c Jan Lellmann, Martin Burger, Jan Modersitzki (Eds.)
264		1	\|a Cham \|b Springer \|c [2019]
264		4	\|c © 2019
300			\|a 1 Online-Ressource (xvii, 574 Seiten) \|b Illustrationen, Diagramme
336			\|b txt \|2 rdacontent
337			\|b c \|2 rdamedia
338			\|b cr \|2 rdacarrier
490	1		\|a Lecture notes in computer science \|v 11603 \|a Image processing, computer vision, pattern recognition, and graphics
650		4	\|a Image Processing and Computer Vision
650		4	\|a Numeric Computing
650		4	\|a Math Applications in Computer Science
650		4	\|a Artificial Intelligence
650		4	\|a Computer vision
650		4	\|a Electronic data processing
650		4	\|a Computer science
650		4	\|a Artificial intelligence
650	0	7	\|a Geometrieverarbeitung \|0 (DE-588)4194224-3 \|2 gnd \|9 rswk-swf
650	0	7	\|a Rauschunterdrückung \|0 (DE-588)4177102-3 \|2 gnd \|9 rswk-swf
650	0	7	\|a Merkmalsextraktion \|0 (DE-588)4314440-8 \|2 gnd \|9 rswk-swf
650	0	7	\|a Level-Set-Methode \|0 (DE-588)4700693-6 \|2 gnd \|9 rswk-swf
650	0	7	\|a Bildverarbeitung \|0 (DE-588)4006684-8 \|2 gnd \|9 rswk-swf
650	0	7	\|a Variationsrechnung \|0 (DE-588)4062355-5 \|2 gnd \|9 rswk-swf
650	0	7	\|a Skalenraum \|0 (DE-588)4510670-8 \|2 gnd \|9 rswk-swf
650	0	7	\|a Maschinelles Sehen \|0 (DE-588)4129594-8 \|2 gnd \|9 rswk-swf
655		7	\|0 (DE-588)1071861417 \|a Konferenzschrift \|y 2019 \|z Hofgeismar \|2 gnd-content
689	0	0	\|a Maschinelles Sehen \|0 (DE-588)4129594-8 \|D s
689	0	1	\|a Merkmalsextraktion \|0 (DE-588)4314440-8 \|D s
689	0	2	\|a Skalenraum \|0 (DE-588)4510670-8 \|D s
689	0	3	\|a Rauschunterdrückung \|0 (DE-588)4177102-3 \|D s
689	0		\|5 DE-604
689	1	0	\|a Bildverarbeitung \|0 (DE-588)4006684-8 \|D s
689	1	1	\|a Geometrieverarbeitung \|0 (DE-588)4194224-3 \|D s
689	1	2	\|a Variationsrechnung \|0 (DE-588)4062355-5 \|D s
689	1	3	\|a Level-Set-Methode \|0 (DE-588)4700693-6 \|D s
689	1		\|5 DE-604
700	1		\|a Lellmann, Jan \|0 (DE-588)1016195257 \|4 edt
700	1		\|a Burger, Martin \|4 edt
700	1		\|a Modersitzki, Jan \|4 edt
776	0	8	\|i Erscheint auch als \|n Druck-Ausgabe \|z 978-3-030-22367-0
776	0	8	\|i Erscheint auch als \|n Druck-Ausgabe \|z 978-3-030-22369-4
830		0	\|a Lecture notes in computer science \|v 11603 : Image processing, computer vision, pattern recognition, and graphics \|w (DE-604)BV014880109 \|9 11603
856	4	0	\|u https://doi.org/10.1007/978-3-030-22368-7 \|x Verlag \|z URL des Erstveröffentlichers \|3 Volltext
912			\|a ZDB-2-SCS
912			\|a ZDB-2-LNC
940	1		\|q ZDB-2-SCS_2019
940	1		\|q ZDB-2-LNC_2019
943	1		\|a oai:aleph.bib-bvb.de:BVB01-031443779
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-634 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-Aug4 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-573 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-M347 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-92 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-898 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-859 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-860 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-861 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-863 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-862 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-523 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-91 \|p ZDB-2-LNC \|q ZDB-2-LNC_2019 \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-473 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-19 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-355 \|p ZDB-2-SCS \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-703 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-20 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-706 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-29 \|p ZDB-2-LNC \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-030-22368-7 \|l DE-739 \|p ZDB-2-LNC \|x Verlag \|3 Volltext

Record in the Search Index

DE-BY-FWS_katkey	730732
_version_	1826989800167571457
adam_text
any_adam_object
author2	Lellmann, Jan Burger, Martin Modersitzki, Jan
author2_role	edt edt edt
author2_variant	j l jl m b mb j m jm
author_GND	(DE-588)1016195257
author_corporate	SSVM Hofgeismar
author_corporate_role	aut
author_facet	Lellmann, Jan Burger, Martin Modersitzki, Jan SSVM Hofgeismar
author_sort	SSVM Hofgeismar
building	Verbundindex
bvnumber	BV046062464
classification_rvk	SS 4800
classification_tum	DAT 760f DAT 000
collection	ZDB-2-SCS ZDB-2-LNC
ctrlnum	(ZDB-2-SCS)9783030223687 (ZDB-2-LNC)9783030223687 (OCoLC)1111824445 (DE-599)BVBBV046062464
dewey-full	006.37 006.6
dewey-hundreds	000 - Computer science, information, general works
dewey-ones	006 - Special computer methods
dewey-raw	006.37 006.6
dewey-search	006.37 006.6
dewey-sort	16.37
dewey-tens	000 - Computer science, information, general works
discipline	Informatik
doi_str_mv	10.1007/978-3-030-22368-7
format	Electronic Conference Proceeding eBook
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000zcb4500</leader><controlfield tag="001">BV046062464</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20250318</controlfield><controlfield tag="007">cr\|uuu---uuuuu</controlfield><controlfield tag="008">190724s2019 xx a\|\|\| o\|\|\|\| 10\|\|\| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783030223687</subfield><subfield code="c">Online</subfield><subfield code="9">978-3-030-22368-7</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-3-030-22368-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-2-SCS)9783030223687</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-2-LNC)9783030223687</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1111824445</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV046062464</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-355</subfield><subfield code="a">DE-860</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-19</subfield><subfield code="a">DE-Aug4</subfield><subfield code="a">DE-898</subfield><subfield code="a">DE-861</subfield><subfield code="a">DE-523</subfield><subfield code="a">DE-859</subfield><subfield code="a">DE-473</subfield><subfield code="a">DE-29</subfield><subfield code="a">DE-863</subfield><subfield code="a">DE-20</subfield><subfield code="a">DE-862</subfield><subfield code="a">DE-92</subfield><subfield code="a">DE-573</subfield><subfield code="a">DE-M347</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-706</subfield><subfield code="a">DE-739</subfield><subfield code="a">DE-634</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.37</subfield><subfield code="2">23</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.6</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">DAT 760f</subfield><subfield code="2">stub</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">DAT 000</subfield><subfield code="2">stub</subfield></datafield><datafield tag="111" ind1="2" ind2=" "><subfield code="a">SSVM</subfield><subfield code="n">7.</subfield><subfield code="d">2019</subfield><subfield code="c">Hofgeismar</subfield><subfield code="j">Verfasser</subfield><subfield code="0">(DE-588)118865389X</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Scale space and variational methods in computer vision</subfield><subfield code="b">7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019 : proceedings</subfield><subfield code="c">Jan Lellmann, Martin Burger, Jan Modersitzki (Eds.)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cham</subfield><subfield code="b">Springer</subfield><subfield code="c">[2019]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2019</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xvii, 574 Seiten)</subfield><subfield code="b">Illustrationen, Diagramme</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Lecture notes in computer science</subfield><subfield code="v">11603</subfield><subfield code="a">Image processing, computer vision, pattern recognition, and graphics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Image Processing and Computer Vision</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Numeric Computing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Math Applications in Computer Science</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial Intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer vision</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Electronic data processing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer science</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Geometrieverarbeitung</subfield><subfield code="0">(DE-588)4194224-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Rauschunterdrückung</subfield><subfield code="0">(DE-588)4177102-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Merkmalsextraktion</subfield><subfield code="0">(DE-588)4314440-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Level-Set-Methode</subfield><subfield code="0">(DE-588)4700693-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Bildverarbeitung</subfield><subfield code="0">(DE-588)4006684-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Variationsrechnung</subfield><subfield code="0">(DE-588)4062355-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Skalenraum</subfield><subfield code="0">(DE-588)4510670-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Maschinelles Sehen</subfield><subfield code="0">(DE-588)4129594-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)1071861417</subfield><subfield code="a">Konferenzschrift</subfield><subfield code="y">2019</subfield><subfield code="z">Hofgeismar</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Maschinelles Sehen</subfield><subfield code="0">(DE-588)4129594-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Merkmalsextraktion</subfield><subfield code="0">(DE-588)4314440-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Skalenraum</subfield><subfield code="0">(DE-588)4510670-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="3"><subfield code="a">Rauschunterdrückung</subfield><subfield code="0">(DE-588)4177102-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="1" ind2="0"><subfield code="a">Bildverarbeitung</subfield><subfield code="0">(DE-588)4006684-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2="1"><subfield code="a">Geometrieverarbeitung</subfield><subfield code="0">(DE-588)4194224-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2="2"><subfield code="a">Variationsrechnung</subfield><subfield code="0">(DE-588)4062355-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2="3"><subfield code="a">Level-Set-Methode</subfield><subfield code="0">(DE-588)4700693-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lellmann, Jan</subfield><subfield code="0">(DE-588)1016195257</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Burger, Martin</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Modersitzki, Jan</subfield><subfield code="4">edt</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-3-030-22367-0</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-3-030-22369-4</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Lecture notes in computer science</subfield><subfield code="v">11603 : Image processing, computer vision, pattern recognition, and graphics</subfield><subfield code="w">(DE-604)BV014880109</subfield><subfield code="9">11603</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SCS</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-LNC</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-SCS_2019</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-LNC_2019</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-031443779</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-634</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-Aug4</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-573</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-M347</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-92</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-898</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-859</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-860</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-861</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-863</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-862</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-523</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-91</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="q">ZDB-2-LNC_2019</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-473</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-19</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-355</subfield><subfield code="p">ZDB-2-SCS</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-703</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-20</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-706</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-29</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-030-22368-7</subfield><subfield code="l">DE-739</subfield><subfield code="p">ZDB-2-LNC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection>
genre	(DE-588)1071861417 Konferenzschrift 2019 Hofgeismar gnd-content
genre_facet	Konferenzschrift 2019 Hofgeismar
id	DE-604.BV046062464
illustrated	Illustrated
indexdate	2025-03-19T04:00:48Z
institution	BVB
institution_GND	(DE-588)118865389X
isbn	9783030223687
language	English
oai_aleph_id	oai:aleph.bib-bvb.de:BVB01-031443779
oclc_num	1111824445
open_access_boolean
owner	DE-355 DE-BY-UBR DE-860 DE-91 DE-BY-TUM DE-19 DE-BY-UBM DE-Aug4 DE-898 DE-BY-UBR DE-861 DE-523 DE-859 DE-473 DE-BY-UBG DE-29 DE-863 DE-BY-FWS DE-20 DE-862 DE-BY-FWS DE-92 DE-573 DE-M347 DE-703 DE-706 DE-739 DE-634
owner_facet	DE-355 DE-BY-UBR DE-860 DE-91 DE-BY-TUM DE-19 DE-BY-UBM DE-Aug4 DE-898 DE-BY-UBR DE-861 DE-523 DE-859 DE-473 DE-BY-UBG DE-29 DE-863 DE-BY-FWS DE-20 DE-862 DE-BY-FWS DE-92 DE-573 DE-M347 DE-703 DE-706 DE-739 DE-634
physical	1 Online-Ressource (xvii, 574 Seiten) Illustrationen, Diagramme
psigel	ZDB-2-SCS ZDB-2-LNC ZDB-2-SCS_2019 ZDB-2-LNC_2019 ZDB-2-LNC ZDB-2-LNC_2019
publishDate	2019
publishDateSearch	2019
publishDateSort	2019
publisher	Springer
record_format	marc
series	Lecture notes in computer science
series2	Lecture notes in computer science Image processing, computer vision, pattern recognition, and graphics
spellingShingle	Scale space and variational methods in computer vision 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019 : proceedings Lecture notes in computer science Image Processing and Computer Vision Numeric Computing Math Applications in Computer Science Artificial Intelligence Computer vision Electronic data processing Computer science Artificial intelligence Geometrieverarbeitung (DE-588)4194224-3 gnd Rauschunterdrückung (DE-588)4177102-3 gnd Merkmalsextraktion (DE-588)4314440-8 gnd Level-Set-Methode (DE-588)4700693-6 gnd Bildverarbeitung (DE-588)4006684-8 gnd Variationsrechnung (DE-588)4062355-5 gnd Skalenraum (DE-588)4510670-8 gnd Maschinelles Sehen (DE-588)4129594-8 gnd
subject_GND	(DE-588)4194224-3 (DE-588)4177102-3 (DE-588)4314440-8 (DE-588)4700693-6 (DE-588)4006684-8 (DE-588)4062355-5 (DE-588)4510670-8 (DE-588)4129594-8 (DE-588)1071861417
title	Scale space and variational methods in computer vision 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019 : proceedings
title_auth	Scale space and variational methods in computer vision 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019 : proceedings
title_exact_search	Scale space and variational methods in computer vision 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019 : proceedings
title_full	Scale space and variational methods in computer vision 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019 : proceedings Jan Lellmann, Martin Burger, Jan Modersitzki (Eds.)
title_fullStr	Scale space and variational methods in computer vision 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019 : proceedings Jan Lellmann, Martin Burger, Jan Modersitzki (Eds.)
title_full_unstemmed	Scale space and variational methods in computer vision 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019 : proceedings Jan Lellmann, Martin Burger, Jan Modersitzki (Eds.)
title_short	Scale space and variational methods in computer vision
title_sort	scale space and variational methods in computer vision 7th international conference ssvm 2019 hofgeismar germany june 30 july 4 2019 proceedings
title_sub	7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 - July 4, 2019 : proceedings
topic	Image Processing and Computer Vision Numeric Computing Math Applications in Computer Science Artificial Intelligence Computer vision Electronic data processing Computer science Artificial intelligence Geometrieverarbeitung (DE-588)4194224-3 gnd Rauschunterdrückung (DE-588)4177102-3 gnd Merkmalsextraktion (DE-588)4314440-8 gnd Level-Set-Methode (DE-588)4700693-6 gnd Bildverarbeitung (DE-588)4006684-8 gnd Variationsrechnung (DE-588)4062355-5 gnd Skalenraum (DE-588)4510670-8 gnd Maschinelles Sehen (DE-588)4129594-8 gnd
topic_facet	Image Processing and Computer Vision Numeric Computing Math Applications in Computer Science Artificial Intelligence Computer vision Electronic data processing Computer science Artificial intelligence Geometrieverarbeitung Rauschunterdrückung Merkmalsextraktion Level-Set-Methode Bildverarbeitung Variationsrechnung Skalenraum Maschinelles Sehen Konferenzschrift 2019 Hofgeismar
url	https://doi.org/10.1007/978-3-030-22368-7
volume_link	(DE-604)BV014880109
work_keys_str_mv	AT ssvmhofgeismar scalespaceandvariationalmethodsincomputervision7thinternationalconferencessvm2019hofgeismargermanyjune30july42019proceedings AT lellmannjan scalespaceandvariationalmethodsincomputervision7thinternationalconferencessvm2019hofgeismargermanyjune30july42019proceedings AT burgermartin scalespaceandvariationalmethodsincomputervision7thinternationalconferencessvm2019hofgeismargermanyjune30july42019proceedings AT modersitzkijan scalespaceandvariationalmethodsincomputervision7thinternationalconferencessvm2019hofgeismargermanyjune30july42019proceedings

Holdings

Get full text

MARC

Record in the Search Index

Similar Items