Deep learning through sparse and low-rank modeling:
Saved in:
| Other Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
London, United Kingdom ; San Diego, CA, United States ; Cambridge, MA, United States ; Oxford, United Kingdom
Academic Press, an imprint of Elsevier
[2019]
|
| Series: | Computer vision and pattern recognition series
|
| Subjects: | |
| Physical Description: | xvii, 277 Seiten Illustrationen, Diagramme |
| ISBN: | 0128136596 9780128136591 |
Staff View
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV045110847 | ||
| 003 | DE-604 | ||
| 005 | 20190520 | ||
| 007 | t| | ||
| 008 | 180801s2019 xx a||| |||| 00||| eng d | ||
| 020 | |a 0128136596 |9 0128136596 | ||
| 020 | |a 9780128136591 |9 978-0-12-813659-1 | ||
| 035 | |a (OCoLC)1101129891 | ||
| 035 | |a (DE-599)BVBBV045110847 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-91G |a DE-20 |a DE-92 |a DE-898 | ||
| 084 | |a ST 302 |0 (DE-625)143652: |2 rvk | ||
| 084 | |a DAT 708f |2 stub | ||
| 245 | 1 | 0 | |a Deep learning through sparse and low-rank modeling |c edited by Zhangyang Wang (Department of Computer Science and Engineering, Texas A&M University, College Station, TX, United States), Yun Fu (Department of Electrical and Computer Engineering and College of Computer and Information Science (Affiliated), Northeastern University, Boston, MA, United States), Thomas S. Huang (Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, United States) |
| 264 | 1 | |a London, United Kingdom ; San Diego, CA, United States ; Cambridge, MA, United States ; Oxford, United Kingdom |b Academic Press, an imprint of Elsevier |c [2019] | |
| 300 | |a xvii, 277 Seiten |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Computer vision and pattern recognition series | |
| 650 | 0 | 7 | |a Deep Learning |0 (DE-588)1135597375 |2 gnd |9 rswk-swf |
| 655 | 7 | |0 (DE-588)4143413-4 |a Aufsatzsammlung |2 gnd-content | |
| 689 | 0 | 0 | |a Deep Learning |0 (DE-588)1135597375 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Wang, Zhangyang |0 (DE-588)1128658186 |4 edt | |
| 700 | 1 | |a Fu, Yun |0 (DE-588)1019266783 |4 edt | |
| 700 | 1 | |a Huang, Thomas S. |4 edt | |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-030501188 | |
Record in the Search Index
| DE-BY-OTHR_call_number | F 03/ST 302 W246 |
|---|---|
| DE-BY-OTHR_katkey | 6171527 |
| DE-BY-OTHR_location | 02 |
| DE-BY-OTHR_media_number | 067004249904 |
| DE-BY-TUM_call_number | 0102 DAT 708f 2019 A 2272 |
| DE-BY-TUM_katkey | 2350459 |
| DE-BY-TUM_location | 01 |
| DE-BY-TUM_media_number | 040008856257 |
| _version_ | 1831256321111883776 |
| adam_text | |
| any_adam_object | |
| author2 | Wang, Zhangyang Fu, Yun Huang, Thomas S. |
| author2_role | edt edt edt |
| author2_variant | z w zw y f yf t s h ts tsh |
| author_GND | (DE-588)1128658186 (DE-588)1019266783 |
| author_facet | Wang, Zhangyang Fu, Yun Huang, Thomas S. |
| building | Verbundindex |
| bvnumber | BV045110847 |
| classification_rvk | ST 302 |
| classification_tum | DAT 708f |
| ctrlnum | (OCoLC)1101129891 (DE-599)BVBBV045110847 |
| discipline | Informatik |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000 c 4500</leader><controlfield tag="001">BV045110847</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20190520</controlfield><controlfield tag="007">t|</controlfield><controlfield tag="008">180801s2019 xx a||| |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">0128136596</subfield><subfield code="9">0128136596</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780128136591</subfield><subfield code="9">978-0-12-813659-1</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1101129891</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV045110847</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-91G</subfield><subfield code="a">DE-20</subfield><subfield code="a">DE-92</subfield><subfield code="a">DE-898</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 302</subfield><subfield code="0">(DE-625)143652:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">DAT 708f</subfield><subfield code="2">stub</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Deep learning through sparse and low-rank modeling</subfield><subfield code="c">edited by Zhangyang Wang (Department of Computer Science and Engineering, Texas A&M University, College Station, TX, United States), Yun Fu (Department of Electrical and Computer Engineering and College of Computer and Information Science (Affiliated), Northeastern University, Boston, MA, United States), Thomas S. Huang (Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, United States)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">London, United Kingdom ; San Diego, CA, United States ; Cambridge, MA, United States ; Oxford, United Kingdom</subfield><subfield code="b">Academic Press, an imprint of Elsevier</subfield><subfield code="c">[2019]</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">xvii, 277 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">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Computer vision and pattern recognition series</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Deep Learning</subfield><subfield code="0">(DE-588)1135597375</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)4143413-4</subfield><subfield code="a">Aufsatzsammlung</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Deep Learning</subfield><subfield code="0">(DE-588)1135597375</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Zhangyang</subfield><subfield code="0">(DE-588)1128658186</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Fu, Yun</subfield><subfield code="0">(DE-588)1019266783</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Huang, Thomas S.</subfield><subfield code="4">edt</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-030501188</subfield></datafield></record></collection> |
| genre | (DE-588)4143413-4 Aufsatzsammlung gnd-content |
| genre_facet | Aufsatzsammlung |
| id | DE-604.BV045110847 |
| illustrated | Illustrated |
| indexdate | 2025-02-13T07:00:22Z |
| institution | BVB |
| isbn | 0128136596 9780128136591 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030501188 |
| oclc_num | 1101129891 |
| open_access_boolean | |
| owner | DE-91G DE-BY-TUM DE-20 DE-92 DE-898 DE-BY-UBR |
| owner_facet | DE-91G DE-BY-TUM DE-20 DE-92 DE-898 DE-BY-UBR |
| physical | xvii, 277 Seiten Illustrationen, Diagramme |
| publishDate | 2019 |
| publishDateSearch | 2019 |
| publishDateSort | 2019 |
| publisher | Academic Press, an imprint of Elsevier |
| record_format | marc |
| series2 | Computer vision and pattern recognition series |
| spellingShingle | Deep learning through sparse and low-rank modeling Deep Learning (DE-588)1135597375 gnd |
| subject_GND | (DE-588)1135597375 (DE-588)4143413-4 |
| title | Deep learning through sparse and low-rank modeling |
| title_auth | Deep learning through sparse and low-rank modeling |
| title_exact_search | Deep learning through sparse and low-rank modeling |
| title_full | Deep learning through sparse and low-rank modeling edited by Zhangyang Wang (Department of Computer Science and Engineering, Texas A&M University, College Station, TX, United States), Yun Fu (Department of Electrical and Computer Engineering and College of Computer and Information Science (Affiliated), Northeastern University, Boston, MA, United States), Thomas S. Huang (Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, United States) |
| title_fullStr | Deep learning through sparse and low-rank modeling edited by Zhangyang Wang (Department of Computer Science and Engineering, Texas A&M University, College Station, TX, United States), Yun Fu (Department of Electrical and Computer Engineering and College of Computer and Information Science (Affiliated), Northeastern University, Boston, MA, United States), Thomas S. Huang (Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, United States) |
| title_full_unstemmed | Deep learning through sparse and low-rank modeling edited by Zhangyang Wang (Department of Computer Science and Engineering, Texas A&M University, College Station, TX, United States), Yun Fu (Department of Electrical and Computer Engineering and College of Computer and Information Science (Affiliated), Northeastern University, Boston, MA, United States), Thomas S. Huang (Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, United States) |
| title_short | Deep learning through sparse and low-rank modeling |
| title_sort | deep learning through sparse and low rank modeling |
| topic | Deep Learning (DE-588)1135597375 gnd |
| topic_facet | Deep Learning Aufsatzsammlung |
| work_keys_str_mv | AT wangzhangyang deeplearningthroughsparseandlowrankmodeling AT fuyun deeplearningthroughsparseandlowrankmodeling AT huangthomass deeplearningthroughsparseandlowrankmodeling |
Order paper/chapter scan
Branch Library Mathematics & Informatics
| Call Number: |
0102 DAT 708f 2019 A 2272
Floor plan |
|---|---|
| Copy 1 | Available for loan On Shelf |