المؤلفون: Hofstädter, Magdalena

مصطلحات موضوعية: Bebauungsformen, Baulandmobilisierung, Innentwicklung vor Außenentwicklung, Building densities, Densification, Baulandreserven, Bebauungsdichten, Building forms, Building land mobilization, Internal development before external development, Nachverdichtung, Building land reserves

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::89e8737a1fc95aebaad2e02c81644a78

المؤلفون: Heinzle, Thomas

مصطلحات موضوعية: Bodenverbrauch, density, Bebauungsplanung, Mindestbaudichte, Mindestbebauungsdichte, Mindestdichte, land consumption, Einfamilienhaus, building densification, Bebauungsdichte, Dichte, minimum building densities, Flächensparen, Verdichtung

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::027e28e76d82db71b0a33ebf6627ea01

المؤلفون: Süberk, Nilay Tuğçe, Ateş, Hasan Fehmi

مصطلحات موضوعية: Bina yoğunluk kestirimi, Derin öğrenme, Uzaktan algılama, Accurate density estimation, Additional training, Building density estimation, Building heat maps, Building locations, Building densities, Buildings, CNN, Comparative simulation, Comparative simulation results, Convolution, Convolutional network, Convolutional neural nets, Convolutional neural network, Deep architectures, Deep learning, Deep learning approaches, Deep learning methods, Density estimation, Geophysical image processing, Learning (artificial intelligence), Learning approach, Network architecture, Neural networks, Optical images, Point-wise estimation, Pre-trained VGG-16

وصف الملف: application/pdf

Relation: 2019 4th International Conference on Computer Science and Engineering (UBMK); Konferans Öğesi - Uluslararası - İdari Personel ve Öğrenci; Suberk, N. T. & Ateş, H. F. (2019). Deep learning for building density estimation in remotely sensed imagery. Paper presented at the 423-428. doi:10.1109/UBMK.2019.8907133; https://hdl.handle.net/11729/2295; http://dx.doi.org/10.1109/UBMK.2019.8907133; 423; 428; N/A; WOS:000609879900080; 2-s2.0-85076199572

الاتاحة: https://hdl.handle.net/11729/2295
https://doi.org/10.1109/UBMK.2019.8907133

المؤلفون: Süberk, Nilay Tuğçe, Ateş, Hasan Fehmi

المساهمون: Işık Üniversitesi, Fen Bilimleri Enstitüsü, Süberk, Nilay Tuğçe

مصطلحات موضوعية: Convolutional network, Learning (artificial intelligence), Time 8.0 s, Building Density Estimation, Comparative simulation results, Derin Öğrenme, Point-wise estimation, Supervised trainings, Convolutional neural network, Building heat maps, Convolutional neural nets, Remotely sensed imagery, Remote sensing optical imagery, Deep learning approaches, Remote Sensing, Optical images, Deep Learning, Learning approach, Pre-trained VGG-16, Density estimation, Buildings, Accurate density estimation, Bina yoğunluk kestirimi, Deep learning methods, Supervised training, Uzaktan Algılama, Network architecture, Bina Yoğunluk Kestirimi, Comparative simulation, Deep learning, Building density estimation, Remote sensing, Uzaktan algılama, Convolution, Derin öğrenme, Building locations, Deep architectures, Building densities, Additional training, CNN, Geophysical image processing, Neural networks

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a6ce779fbcddc099bc5060772733039e
https://hdl.handle.net/11729/2295

المؤلفون: DE VECCHI, DANIELE, DELL'ACQUA, FABIO

المساهمون: DE VECCHI, Daniele, Dell'Acqua, Fabio

مصطلحات موضوعية: Classification (of information), Damage detection, Disasters, Radar, Radar imaging, Risk assessment, Statistical methods, Building densities, Damage assessments, Damage distribution, Natural disasters, Operational methods, Priori information, Radar backscatter, Urban structure

وصف الملف: ELETTRONICO

Relation: info:eu-repo/semantics/altIdentifier/isbn/978-380074228-8; info:eu-repo/semantics/altIdentifier/wos/WOS:000388020600115; ispartofbook:Proc. of EUSAR 2016; EUSAR 2016: 11th European Conference on Synthetic Aperture Radar; http://hdl.handle.net/11571/1182964; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85000997325; http://ieeexplore.ieee.org/document/7559345/#full-text-section

الاتاحة: http://hdl.handle.net/11571/1182964
http://ieeexplore.ieee.org/document/7559345/#full-text-section