Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik / / Norbert Mitschke.

In the first part of this dissertation, a framework for the design of a CNN for FPGAs is presented, consisting of a preprocessing algorithm, an augmentation technique, a custom quantization scheme and a pruning step of the CNN. The combination of conventional image processing with neural networks is...

Full description

Saved in:
Bibliographic Details
VerfasserIn:
Place / Publishing House:[Place of publication not identified] : : KIT Scientific Publishing,, 2022.
Year of Publication:2022
Language:German
Physical Description:1 online resource (212 pages)
Tags: Add Tag
No Tags, Be the first to tag this record!
id 993555376804498
ctrlnum (CKB)5700000000114322
(NjHacI)995700000000114322
(EXLCZ)995700000000114322
collection bib_alma
record_format marc
spelling Mitschke, Norbert, author.
Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik / Norbert Mitschke.
[Place of publication not identified] : KIT Scientific Publishing, 2022.
1 online resource (212 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Description based on publisher supplied metadata and other sources.
In the first part of this dissertation, a framework for the design of a CNN for FPGAs is presented, consisting of a preprocessing algorithm, an augmentation technique, a custom quantization scheme and a pruning step of the CNN. The combination of conventional image processing with neural networks is shown in the second part by an example from robotics, where an image-based visual servoing process is successfully conducted for a gripping process of a robot.
Electrical engineering.
1000146397
language German
format eBook
author Mitschke, Norbert,
spellingShingle Mitschke, Norbert,
Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik /
author_facet Mitschke, Norbert,
author_variant n m nm
author_role VerfasserIn
author_sort Mitschke, Norbert,
title Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik /
title_full Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik / Norbert Mitschke.
title_fullStr Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik / Norbert Mitschke.
title_full_unstemmed Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik / Norbert Mitschke.
title_auth Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik /
title_new Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik /
title_sort konvolutionäre neuronale netze in der industriellen bildverarbeitung und robotik /
publisher KIT Scientific Publishing,
publishDate 2022
physical 1 online resource (212 pages)
isbn 1000146397
callnumber-first T - Technology
callnumber-subject TK - Electrical and Nuclear Engineering
callnumber-label TK146
callnumber-sort TK 3146 M587 42022
illustrated Not Illustrated
dewey-hundreds 600 - Technology
dewey-tens 620 - Engineering
dewey-ones 621 - Applied physics
dewey-full 621.3
dewey-sort 3621.3
dewey-raw 621.3
dewey-search 621.3
work_keys_str_mv AT mitschkenorbert konvolutionareneuronalenetzeinderindustriellenbildverarbeitungundrobotik
status_str n
ids_txt_mv (CKB)5700000000114322
(NjHacI)995700000000114322
(EXLCZ)995700000000114322
carrierType_str_mv cr
is_hierarchy_title Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik /
_version_ 1787552597190639616
fullrecord <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01408nam a2200277 4500</leader><controlfield tag="001">993555376804498</controlfield><controlfield tag="005">20230221171034.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr |||||||||||</controlfield><controlfield tag="008">230221s2022 xx o 000 0 ger d</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)5700000000114322</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(NjHacI)995700000000114322</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)995700000000114322</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">NjHacI</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="c">NjHacl</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">TK146</subfield><subfield code="b">.M587 2022</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">621.3</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Mitschke, Norbert,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik /</subfield><subfield code="c">Norbert Mitschke.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">[Place of publication not identified] :</subfield><subfield code="b">KIT Scientific Publishing,</subfield><subfield code="c">2022.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (212 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In the first part of this dissertation, a framework for the design of a CNN for FPGAs is presented, consisting of a preprocessing algorithm, an augmentation technique, a custom quantization scheme and a pruning step of the CNN. The combination of conventional image processing with neural networks is shown in the second part by an example from robotics, where an image-based visual servoing process is successfully conducted for a gripping process of a robot.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Electrical engineering.</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">1000146397</subfield></datafield><datafield tag="906" ind1=" " ind2=" "><subfield code="a">BOOK</subfield></datafield><datafield tag="ADM" ind1=" " ind2=" "><subfield code="b">2023-03-01 00:17:06 Europe/Vienna</subfield><subfield code="f">system</subfield><subfield code="c">marc21</subfield><subfield code="a">2022-09-03 21:29:14 Europe/Vienna</subfield><subfield code="g">false</subfield></datafield><datafield tag="AVE" ind1=" " ind2=" "><subfield code="i">DOAB Directory of Open Access Books</subfield><subfield code="P">DOAB Directory of Open Access Books</subfield><subfield code="x">https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&amp;portfolio_pid=5339742670004498&amp;Force_direct=true</subfield><subfield code="Z">5339742670004498</subfield><subfield code="b">Available</subfield><subfield code="8">5339742670004498</subfield></datafield></record></collection>