Granular video computing: with rough sets, deep learning and in IoT
"This volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Singapore
World Scientific
2021
|
| Schlagworte: | |
| Online-Zugang: | FHI01 Volltext |
| Zusammenfassung: | "This volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such as object tracking from videos in constrained situations, occlusion/overlapping handling, measuring of the reliability of tracking methods, object recognition and linguistic interpretation in video scenes, and event prediction from videos, are the addressed in this volume. The book also looks at ways to reduce data dependency in the context of unsupervised (without manual interaction/ labeled data/ prior information) training. This book may be used both as a textbook and reference book for graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology, and is recommended for both students and practitioners working in computer vision, machine learning, video analytics, image analytics, artificial intelligence, system design, rough set theory, granular computing, and soft computing"--Publisher's website |
| Beschreibung: | 1 Online-Ressource (xxxi, 223 Seiten) |
| ISBN: | 9789811227127 9789811227134 |
| DOI: | 10.1142/12013 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV047192439 | ||
| 003 | DE-604 | ||
| 005 | 20230530 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 210311s2021 |||| o||u| ||||||eng d | ||
| 020 | |a 9789811227127 |9 978-981-122-712-7 | ||
| 020 | |a 9789811227134 |9 978-981-122-713-4 | ||
| 035 | |a (ZDB-124-WOP)00012013 | ||
| 035 | |a (OCoLC)1241682486 | ||
| 035 | |a (DE-599)BVBBV047192439 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-573 | ||
| 082 | 0 | |a 006.7 | |
| 100 | 1 | |a Chakraborty, Debarati B. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Granular video computing |b with rough sets, deep learning and in IoT |c Debarati B Chakraborty, Sankar K Pal |
| 264 | 1 | |a Singapore |b World Scientific |c 2021 | |
| 300 | |a 1 Online-Ressource (xxxi, 223 Seiten) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 520 | |a "This volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such as object tracking from videos in constrained situations, occlusion/overlapping handling, measuring of the reliability of tracking methods, object recognition and linguistic interpretation in video scenes, and event prediction from videos, are the addressed in this volume. The book also looks at ways to reduce data dependency in the context of unsupervised (without manual interaction/ labeled data/ prior information) training. This book may be used both as a textbook and reference book for graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology, and is recommended for both students and practitioners working in computer vision, machine learning, video analytics, image analytics, artificial intelligence, system design, rough set theory, granular computing, and soft computing"--Publisher's website | ||
| 650 | 4 | |a Computer vision | |
| 650 | 4 | |a Automatic tracking | |
| 653 | |a Electronic books | ||
| 700 | 1 | |a Pal, Sankar K. |d 1950- |e Verfasser |0 (DE-588)121101622 |4 aut | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9789811227110 |
| 856 | 4 | 0 | |u https://doi.org/10.1142/12013 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-124-WOP | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-032597604 | ||
| 966 | e | |u https://doi.org/10.1142/12013 |l FHI01 |p ZDB-124-WOP |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804182292203044864 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Chakraborty, Debarati B. Pal, Sankar K. 1950- |
| author_GND | (DE-588)121101622 |
| author_facet | Chakraborty, Debarati B. Pal, Sankar K. 1950- |
| author_role | aut aut |
| author_sort | Chakraborty, Debarati B. |
| author_variant | d b c db dbc s k p sk skp |
| building | Verbundindex |
| bvnumber | BV047192439 |
| collection | ZDB-124-WOP |
| ctrlnum | (ZDB-124-WOP)00012013 (OCoLC)1241682486 (DE-599)BVBBV047192439 |
| dewey-full | 006.7 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.7 |
| dewey-search | 006.7 |
| dewey-sort | 16.7 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| doi_str_mv | 10.1142/12013 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02555nmm a2200397zc 4500</leader><controlfield tag="001">BV047192439</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20230530 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">210311s2021 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9789811227127</subfield><subfield code="9">978-981-122-712-7</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9789811227134</subfield><subfield code="9">978-981-122-713-4</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-124-WOP)00012013</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1241682486</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047192439</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-573</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.7</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Chakraborty, Debarati B.</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Granular video computing</subfield><subfield code="b">with rough sets, deep learning and in IoT</subfield><subfield code="c">Debarati B Chakraborty, Sankar K Pal</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Singapore</subfield><subfield code="b">World Scientific</subfield><subfield code="c">2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xxxi, 223 Seiten)</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="520" ind1=" " ind2=" "><subfield code="a">"This volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such as object tracking from videos in constrained situations, occlusion/overlapping handling, measuring of the reliability of tracking methods, object recognition and linguistic interpretation in video scenes, and event prediction from videos, are the addressed in this volume. The book also looks at ways to reduce data dependency in the context of unsupervised (without manual interaction/ labeled data/ prior information) training. This book may be used both as a textbook and reference book for graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology, and is recommended for both students and practitioners working in computer vision, machine learning, video analytics, image analytics, artificial intelligence, system design, rough set theory, granular computing, and soft computing"--Publisher's website</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer vision</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Automatic tracking</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Electronic books</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Pal, Sankar K.</subfield><subfield code="d">1950-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)121101622</subfield><subfield code="4">aut</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">9789811227110</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1142/12013</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-124-WOP</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-032597604</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1142/12013</subfield><subfield code="l">FHI01</subfield><subfield code="p">ZDB-124-WOP</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV047192439 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:48:23Z |
| indexdate | 2024-07-10T09:05:14Z |
| institution | BVB |
| isbn | 9789811227127 9789811227134 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032597604 |
| oclc_num | 1241682486 |
| open_access_boolean | |
| owner | DE-573 |
| owner_facet | DE-573 |
| physical | 1 Online-Ressource (xxxi, 223 Seiten) |
| psigel | ZDB-124-WOP |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | World Scientific |
| record_format | marc |
| spelling | Chakraborty, Debarati B. Verfasser aut Granular video computing with rough sets, deep learning and in IoT Debarati B Chakraborty, Sankar K Pal Singapore World Scientific 2021 1 Online-Ressource (xxxi, 223 Seiten) txt rdacontent c rdamedia cr rdacarrier "This volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such as object tracking from videos in constrained situations, occlusion/overlapping handling, measuring of the reliability of tracking methods, object recognition and linguistic interpretation in video scenes, and event prediction from videos, are the addressed in this volume. The book also looks at ways to reduce data dependency in the context of unsupervised (without manual interaction/ labeled data/ prior information) training. This book may be used both as a textbook and reference book for graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology, and is recommended for both students and practitioners working in computer vision, machine learning, video analytics, image analytics, artificial intelligence, system design, rough set theory, granular computing, and soft computing"--Publisher's website Computer vision Automatic tracking Electronic books Pal, Sankar K. 1950- Verfasser (DE-588)121101622 aut Erscheint auch als Druck-Ausgabe 9789811227110 https://doi.org/10.1142/12013 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Chakraborty, Debarati B. Pal, Sankar K. 1950- Granular video computing with rough sets, deep learning and in IoT Computer vision Automatic tracking |
| title | Granular video computing with rough sets, deep learning and in IoT |
| title_auth | Granular video computing with rough sets, deep learning and in IoT |
| title_exact_search | Granular video computing with rough sets, deep learning and in IoT |
| title_exact_search_txtP | Granular video computing with rough sets, deep learning and in IoT |
| title_full | Granular video computing with rough sets, deep learning and in IoT Debarati B Chakraborty, Sankar K Pal |
| title_fullStr | Granular video computing with rough sets, deep learning and in IoT Debarati B Chakraborty, Sankar K Pal |
| title_full_unstemmed | Granular video computing with rough sets, deep learning and in IoT Debarati B Chakraborty, Sankar K Pal |
| title_short | Granular video computing |
| title_sort | granular video computing with rough sets deep learning and in iot |
| title_sub | with rough sets, deep learning and in IoT |
| topic | Computer vision Automatic tracking |
| topic_facet | Computer vision Automatic tracking |
| url | https://doi.org/10.1142/12013 |
| work_keys_str_mv | AT chakrabortydebaratib granularvideocomputingwithroughsetsdeeplearningandiniot AT palsankark granularvideocomputingwithroughsetsdeeplearningandiniot |