Deep learning methods for remote sensing:
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Basel
MDPI
[2022]
|
| Schlagworte: | |
| Online-Zugang: | Volltext Volltext |
| Beschreibung: | Printed edition of the special issue published in Sensors |
| Beschreibung: | 1 Online-Ressource (IX, 331 Seiten) Illustrationen, Diagramme |
| ISBN: | 9783036546308 |
Internformat
MARC
| LEADER | 00000nmm a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV048670990 | ||
| 003 | DE-604 | ||
| 005 | 20230123 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 230123s2022 |||| o||u| ||||||eng d | ||
| 020 | |a 9783036546308 |9 978-3-0365-4630-8 | ||
| 024 | 7 | |a 10.3390/books978-3-0365-4630-8 |2 doi | |
| 035 | |a (OCoLC)1369567240 | ||
| 035 | |a (DE-599)BVBBV048670990 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-12 |a DE-210 |a DE-521 |a DE-1102 |a DE-1046 |a DE-1028 |a DE-1050 |a DE-573 |a DE-M347 |a DE-92 |a DE-1051 |a DE-898 |a DE-859 |a DE-860 |a DE-1049 |a DE-863 |a DE-862 |a DE-Re13 |a DE-Y3 |a DE-255 |a DE-Y7 |a DE-Y2 |a DE-70 |a DE-2174 |a DE-127 |a DE-22 |a DE-155 |a DE-91 |a DE-384 |a DE-473 |a DE-19 |a DE-355 |a DE-703 |a DE-20 |a DE-706 |a DE-824 |a DE-29 |a DE-739 | ||
| 245 | 1 | 0 | |a Deep learning methods for remote sensing |c editors Moulay A. Akhloufi, Mozhdeh Shahbazi |
| 264 | 1 | |a Basel |b MDPI |c [2022] | |
| 300 | |a 1 Online-Ressource (IX, 331 Seiten) |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a Printed edition of the special issue published in Sensors | ||
| 650 | 0 | 7 | |a Deep learning |0 (DE-588)1135597375 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Fernerkundung |0 (DE-588)4016796-3 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Umwelttechnik |0 (DE-588)4061650-2 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Umweltwissenschaften |0 (DE-588)4137364-9 |2 gnd |9 rswk-swf |
| 655 | 7 | |0 (DE-588)4143413-4 |a Aufsatzsammlung |2 gnd-content | |
| 689 | 0 | 0 | |a Umweltwissenschaften |0 (DE-588)4137364-9 |D s |
| 689 | 0 | 1 | |a Umwelttechnik |0 (DE-588)4061650-2 |D s |
| 689 | 0 | 2 | |a Fernerkundung |0 (DE-588)4016796-3 |D s |
| 689 | 0 | 3 | |a Deep learning |0 (DE-588)1135597375 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Akhloufi, Moulay A. |4 edt | |
| 700 | 1 | |a Shahbazi, Mozhdeh |4 edt | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-3-0365-4629-2 |
| 856 | 4 | 0 | |u https://www.mdpi.com/books/book/6279 |x Verlag |z kostenfrei |3 Volltext |
| 856 | 4 | 0 | |u https://directory.doabooks.org/handle/20.500.12854/93850 |x Verlag |z kostenfrei |3 Volltext |
| 912 | |a ZDB-94-OAB | ||
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-034045560 | |
Datensatz im Suchindex
| _version_ | 1813306171911569408 |
|---|---|
| adam_text | |
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author2 | Akhloufi, Moulay A. Shahbazi, Mozhdeh |
| author2_role | edt edt |
| author2_variant | m a a ma maa m s ms |
| author_facet | Akhloufi, Moulay A. Shahbazi, Mozhdeh |
| building | Verbundindex |
| bvnumber | BV048670990 |
| collection | ZDB-94-OAB |
| ctrlnum | (OCoLC)1369567240 (DE-599)BVBBV048670990 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nmm a2200000 c 4500</leader><controlfield tag="001">BV048670990</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20230123</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">230123s2022 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783036546308</subfield><subfield code="9">978-3-0365-4630-8</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/books978-3-0365-4630-8</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1369567240</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV048670990</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-12</subfield><subfield code="a">DE-210</subfield><subfield code="a">DE-521</subfield><subfield code="a">DE-1102</subfield><subfield code="a">DE-1046</subfield><subfield code="a">DE-1028</subfield><subfield code="a">DE-1050</subfield><subfield code="a">DE-573</subfield><subfield code="a">DE-M347</subfield><subfield code="a">DE-92</subfield><subfield code="a">DE-1051</subfield><subfield code="a">DE-898</subfield><subfield code="a">DE-859</subfield><subfield code="a">DE-860</subfield><subfield code="a">DE-1049</subfield><subfield code="a">DE-863</subfield><subfield code="a">DE-862</subfield><subfield code="a">DE-Re13</subfield><subfield code="a">DE-Y3</subfield><subfield code="a">DE-255</subfield><subfield code="a">DE-Y7</subfield><subfield code="a">DE-Y2</subfield><subfield code="a">DE-70</subfield><subfield code="a">DE-2174</subfield><subfield code="a">DE-127</subfield><subfield code="a">DE-22</subfield><subfield code="a">DE-155</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-384</subfield><subfield code="a">DE-473</subfield><subfield code="a">DE-19</subfield><subfield code="a">DE-355</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-20</subfield><subfield code="a">DE-706</subfield><subfield code="a">DE-824</subfield><subfield code="a">DE-29</subfield><subfield code="a">DE-739</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Deep learning methods for remote sensing</subfield><subfield code="c">editors Moulay A. Akhloufi, Mozhdeh Shahbazi</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Basel</subfield><subfield code="b">MDPI</subfield><subfield code="c">[2022]</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (IX, 331 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="500" ind1=" " ind2=" "><subfield code="a">Printed edition of the special issue published in Sensors</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="650" ind1="0" ind2="7"><subfield code="a">Fernerkundung</subfield><subfield code="0">(DE-588)4016796-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Umwelttechnik</subfield><subfield code="0">(DE-588)4061650-2</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Umweltwissenschaften</subfield><subfield code="0">(DE-588)4137364-9</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">Umweltwissenschaften</subfield><subfield code="0">(DE-588)4137364-9</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Umwelttechnik</subfield><subfield code="0">(DE-588)4061650-2</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Fernerkundung</subfield><subfield code="0">(DE-588)4016796-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="3"><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">Akhloufi, Moulay A.</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Shahbazi, Mozhdeh</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">978-3-0365-4629-2</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/books/book/6279</subfield><subfield code="x">Verlag</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://directory.doabooks.org/handle/20.500.12854/93850</subfield><subfield code="x">Verlag</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-94-OAB</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034045560</subfield></datafield></record></collection> |
| genre | (DE-588)4143413-4 Aufsatzsammlung gnd-content |
| genre_facet | Aufsatzsammlung |
| id | DE-604.BV048670990 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T21:22:48Z |
| indexdate | 2024-10-19T04:05:23Z |
| institution | BVB |
| isbn | 9783036546308 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034045560 |
| oclc_num | 1369567240 |
| open_access_boolean | 1 |
| owner | DE-12 DE-210 DE-521 DE-1102 DE-1046 DE-1028 DE-1050 DE-573 DE-M347 DE-92 DE-1051 DE-898 DE-BY-UBR DE-859 DE-860 DE-1049 DE-863 DE-BY-FWS DE-862 DE-BY-FWS DE-Re13 DE-BY-UBR DE-Y3 DE-255 DE-Y7 DE-Y2 DE-70 DE-2174 DE-127 DE-22 DE-BY-UBG DE-155 DE-BY-UBR DE-91 DE-BY-TUM DE-384 DE-473 DE-BY-UBG DE-19 DE-BY-UBM DE-355 DE-BY-UBR DE-703 DE-20 DE-706 DE-824 DE-29 DE-739 |
| owner_facet | DE-12 DE-210 DE-521 DE-1102 DE-1046 DE-1028 DE-1050 DE-573 DE-M347 DE-92 DE-1051 DE-898 DE-BY-UBR DE-859 DE-860 DE-1049 DE-863 DE-BY-FWS DE-862 DE-BY-FWS DE-Re13 DE-BY-UBR DE-Y3 DE-255 DE-Y7 DE-Y2 DE-70 DE-2174 DE-127 DE-22 DE-BY-UBG DE-155 DE-BY-UBR DE-91 DE-BY-TUM DE-384 DE-473 DE-BY-UBG DE-19 DE-BY-UBM DE-355 DE-BY-UBR DE-703 DE-20 DE-706 DE-824 DE-29 DE-739 |
| physical | 1 Online-Ressource (IX, 331 Seiten) Illustrationen, Diagramme |
| psigel | ZDB-94-OAB |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI |
| record_format | marc |
| spellingShingle | Deep learning methods for remote sensing Deep learning (DE-588)1135597375 gnd Fernerkundung (DE-588)4016796-3 gnd Umwelttechnik (DE-588)4061650-2 gnd Umweltwissenschaften (DE-588)4137364-9 gnd |
| subject_GND | (DE-588)1135597375 (DE-588)4016796-3 (DE-588)4061650-2 (DE-588)4137364-9 (DE-588)4143413-4 |
| title | Deep learning methods for remote sensing |
| title_auth | Deep learning methods for remote sensing |
| title_exact_search | Deep learning methods for remote sensing |
| title_exact_search_txtP | Deep learning methods for remote sensing |
| title_full | Deep learning methods for remote sensing editors Moulay A. Akhloufi, Mozhdeh Shahbazi |
| title_fullStr | Deep learning methods for remote sensing editors Moulay A. Akhloufi, Mozhdeh Shahbazi |
| title_full_unstemmed | Deep learning methods for remote sensing editors Moulay A. Akhloufi, Mozhdeh Shahbazi |
| title_short | Deep learning methods for remote sensing |
| title_sort | deep learning methods for remote sensing |
| topic | Deep learning (DE-588)1135597375 gnd Fernerkundung (DE-588)4016796-3 gnd Umwelttechnik (DE-588)4061650-2 gnd Umweltwissenschaften (DE-588)4137364-9 gnd |
| topic_facet | Deep learning Fernerkundung Umwelttechnik Umweltwissenschaften Aufsatzsammlung |
| url | https://www.mdpi.com/books/book/6279 https://directory.doabooks.org/handle/20.500.12854/93850 |
| work_keys_str_mv | AT akhloufimoulaya deeplearningmethodsforremotesensing AT shahbazimozhdeh deeplearningmethodsforremotesensing |