Composing Fisher Kernels from deep neural models: a practitioner's approach
Gespeichert in:
Hauptverfasser: | , |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Cham
Springer
[2018]
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Schriftenreihe: | SpringerBriefs in computer science
|
Schlagworte: | |
Online-Zugang: | BTU01 FHA01 FHI01 FHM01 FHN01 FHR01 FKE01 FLA01 FRO01 FWS01 FWS02 HTW01 UBG01 UBM01 UBR01 UBT01 UBW01 UBY01 UER01 UPA01 Volltext |
Beschreibung: | 1 Online-Ressource (XIII, 59 Seiten, 6 illus., 5 illus. in color) |
ISBN: | 9783319985244 |
ISSN: | 2191-5768 |
DOI: | 10.1007/978-3-319-98524-4 |
Internformat
MARC
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Datensatz im Suchindex
DE-BY-FWS_katkey | 700269 |
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any_adam_object | |
author | Azim, Tayyaba Ahmed, Sarah |
author_facet | Azim, Tayyaba Ahmed, Sarah |
author_role | aut aut |
author_sort | Azim, Tayyaba |
author_variant | t a ta s a sa |
building | Verbundindex |
bvnumber | BV045165067 |
collection | ZDB-2-SCS |
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dewey-full | 006.4 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 006 - Special computer methods |
dewey-raw | 006.4 |
dewey-search | 006.4 |
dewey-sort | 16.4 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
doi_str_mv | 10.1007/978-3-319-98524-4 |
format | Electronic eBook |
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illustrated | Not Illustrated |
indexdate | 2024-08-01T13:32:07Z |
institution | BVB |
isbn | 9783319985244 |
issn | 2191-5768 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030554474 |
oclc_num | 1050948996 |
open_access_boolean | |
owner | DE-355 DE-BY-UBR DE-860 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-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 (XIII, 59 Seiten, 6 illus., 5 illus. in color) |
psigel | ZDB-2-SCS ZDB-2-SCS_2018 |
publishDate | 2018 |
publishDateSearch | 2018 |
publishDateSort | 2018 |
publisher | Springer |
record_format | marc |
series2 | SpringerBriefs in computer science |
spellingShingle | Azim, Tayyaba Ahmed, Sarah Composing Fisher Kernels from deep neural models a practitioner's approach Pattern Recognition Signal, Image and Speech Processing Information Storage and Retrieval Probability and Statistics in Computer Science Data Storage Representation Artificial Intelligence (incl. Robotics) Optical pattern recognition Information storage and retrieva Computer science Artificial intelligence |
title | Composing Fisher Kernels from deep neural models a practitioner's approach |
title_auth | Composing Fisher Kernels from deep neural models a practitioner's approach |
title_exact_search | Composing Fisher Kernels from deep neural models a practitioner's approach |
title_full | Composing Fisher Kernels from deep neural models a practitioner's approach Tayyaba Azim, Sarah Ahmed |
title_fullStr | Composing Fisher Kernels from deep neural models a practitioner's approach Tayyaba Azim, Sarah Ahmed |
title_full_unstemmed | Composing Fisher Kernels from deep neural models a practitioner's approach Tayyaba Azim, Sarah Ahmed |
title_short | Composing Fisher Kernels from deep neural models |
title_sort | composing fisher kernels from deep neural models a practitioner s approach |
title_sub | a practitioner's approach |
topic | Pattern Recognition Signal, Image and Speech Processing Information Storage and Retrieval Probability and Statistics in Computer Science Data Storage Representation Artificial Intelligence (incl. Robotics) Optical pattern recognition Information storage and retrieva Computer science Artificial intelligence |
topic_facet | Pattern Recognition Signal, Image and Speech Processing Information Storage and Retrieval Probability and Statistics in Computer Science Data Storage Representation Artificial Intelligence (incl. Robotics) Optical pattern recognition Information storage and retrieva Computer science Artificial intelligence |
url | https://doi.org/10.1007/978-3-319-98524-4 |
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