Remote Sensing based Building Extraction / / edited by Mohammad Awrangjeb, [and three others].
Building extraction from remote sensing data plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Even though significant research has been carried out for more than two decades, the success of automatic...
Saved in:
TeilnehmendeR: | |
---|---|
Place / Publishing House: | Basel, Switzerland : : MDPI - Multidisciplinary Digital Publishing Institute,, 2020. |
Year of Publication: | 2020 |
Language: | English |
Physical Description: | 1 online resource (442 pages) :; illustrations |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
LEADER | 01889nam a2200289 i 4500 | ||
---|---|---|---|
001 | 993561948404498 | ||
005 | 20230221131807.0 | ||
006 | m o d | ||
007 | cr ||||||||||| | ||
008 | 230221s2020 sz a o 000 0 eng d | ||
035 | |a (CKB)4920000001372603 | ||
035 | |a (NjHacI)994920000001372603 | ||
035 | |a (EXLCZ)994920000001372603 | ||
040 | |a NjHacI |b eng |e rda |c NjHacl | ||
050 | 4 | |a G70.4 |b .R466 2020 | |
082 | 0 | 4 | |a 621.3678 |2 23 |
245 | 0 | 0 | |a Remote Sensing based Building Extraction / |c edited by Mohammad Awrangjeb, [and three others]. |
264 | 1 | |a Basel, Switzerland : |b MDPI - Multidisciplinary Digital Publishing Institute, |c 2020. | |
300 | |a 1 online resource (442 pages) : |b illustrations | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
588 | |a Description based on publisher supplied metadata and other sources. | ||
520 | |a Building extraction from remote sensing data plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Even though significant research has been carried out for more than two decades, the success of automatic building extraction and modeling is still largely impeded by scene complexity, incomplete cue extraction, and sensor dependency of data. Most recently, deep neural networks (DNN) have been widely applied for high classification accuracy in various areas including land-cover and land-use classification. Therefore, intelligent and innovative algorithms are needed for the success of automatic building extraction and modeling. This Special Issue focuses on newly developed methods for classification and feature extraction from remote sensing data for automatic building extraction and 3D. | ||
650 | 0 | |a Civil engineering. | |
650 | 0 | |a Remote sensing. | |
776 | |z 3-03928-383-9 | ||
700 | 1 | |a Awrangjeb, Mohammad, |e editor. | |
906 | |a BOOK | ||
ADM | |b 2023-03-01 00:18:43 Europe/Vienna |f system |c marc21 |a 2022-09-22 08:09:39 Europe/Vienna |g false | ||
AVE | |P DOAB Directory of Open Access Books |x https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5338877370004498&Force_direct=true |Z 5338877370004498 |8 5338877370004498 |