{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T15:31:20Z","timestamp":1759159880178,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":80,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T00:00:00Z","timestamp":1575244800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,12,2]]},"DOI":"10.1145\/3366030.3368456","type":"proceedings-article","created":{"date-parts":[[2020,2,22]],"date-time":"2020-02-22T12:18:47Z","timestamp":1582373927000},"page":"502-511","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Building Extraction from Google Earth Images"],"prefix":"10.1145","author":[{"given":"Jifang","family":"Xing","sequence":"first","affiliation":[{"name":"National University of Singapore"}]},{"given":"Zhang","family":"Ruixi","sequence":"additional","affiliation":[{"name":"National University of Singapore"}]},{"given":"Remmy","family":"Zen","sequence":"additional","affiliation":[{"name":"National University of Singapore"}]},{"given":"Dewa Made Sri","family":"Arsa","sequence":"additional","affiliation":[{"name":"Udayana University"}]},{"given":"Ismail","family":"Khalil","sequence":"additional","affiliation":[{"name":"Johannes Kepler University"}]},{"given":"St\u00e9phane","family":"Bressan","sequence":"additional","affiliation":[{"name":"National University of Singapore"}]}],"member":"320","published-online":{"date-parts":[[2020,2,22]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_3_2_1_1_1","DOI":"10.1109\/IGARSS.2015.7326162"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_2_1","DOI":"10.1109\/PRRS.2008.4783173"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_3_1","DOI":"10.1109\/ICRAMET.2017.8253139"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_4_1","DOI":"10.1109\/ICCSP.2017.8286426"},{"unstructured":"The Image Analysis and Data Fusion Technical Committee. 2015. GRSS Data Fusion Contest. IEEE. http:\/\/www.grss-ieee.org\/community\/technical-committees\/data-fusion The Image Analysis and Data Fusion Technical Committee. 2015. GRSS Data Fusion Contest. IEEE. http:\/\/www.grss-ieee.org\/community\/technical-committees\/data-fusion","key":"e_1_3_2_1_5_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_6_1","DOI":"10.1109\/TGRS.2014.2299540"},{"volume-title":"Segnet: A deep convolutional encoder-decoder architecture for image segmentation","year":"2017","author":"Badrinarayanan Vijay","key":"e_1_3_2_1_7_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_8_1","DOI":"10.1109\/ICMCS.2014.6911229"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_9_1","DOI":"10.1109\/ICIP.2019.8803050"},{"unstructured":"Zhang Bo Wang Chao Zhang Hong and Wu Fan. 2012. A review on building extraction and Reconstruction from SAR image. Zhang Bo Wang Chao Zhang Hong and Wu Fan. 2012. A review on building extraction and Reconstruction from SAR image.","key":"e_1_3_2_1_10_1"},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. IEEE, 1--9.","year":"2019","author":"Bonafilia Derrick","key":"e_1_3_2_1_11_1"},{"unstructured":"Kyle Bradbury Benjamin Brigman Leslie Collins Timothy Johnson Sebastian Lin Richard Newell Sophia Park Sunith Suresh Hoel Wiesner and Yue Xi. 2016. Aerial imagery object identification dataset for building and road detection and building height estimation. Kyle Bradbury Benjamin Brigman Leslie Collins Timothy Johnson Sebastian Lin Richard Newell Sophia Park Sunith Suresh Hoel Wiesner and Yue Xi. 2016. Aerial imagery object identification dataset for building and road detection and building height estimation.","key":"e_1_3_2_1_12_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_13_1","DOI":"10.1109\/IGARSS.2017.8127295"},{"volume-title":"Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs","year":"2017","author":"Chen Liang-Chieh","key":"e_1_3_2_1_14_1"},{"doi-asserted-by":"crossref","unstructured":"Qi Chen Lei Wang Yifan Wu Guangming Wu Zhiling Guo and Steven L Waslander. 2019. Aerial imagery for roof segmentation: A large-scale dataset towards automatic mapping of buildings. ISPRS journal of photogrammetry and remote sensing 147 (2019) 42--55. Qi Chen Lei Wang Yifan Wu Guangming Wu Zhiling Guo and Steven L Waslander. 2019. Aerial imagery for roof segmentation: A large-scale dataset towards automatic mapping of buildings. ISPRS journal of photogrammetry and remote sensing 147 (2019) 42--55.","key":"e_1_3_2_1_15_1","DOI":"10.1016\/j.isprsjprs.2018.11.011"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_16_1","DOI":"10.1016\/j.isprsjprs.2016.03.014"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_17_1","DOI":"10.3390\/rs8080689"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_18_1","DOI":"10.1109\/CVPRW.2018.00031"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_19_1","DOI":"10.1016\/j.isprsjprs.2017.06.005"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_20_1","DOI":"10.1109\/CVPR.2016.265"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_21_1","DOI":"10.1016\/j.isprsjprs.2014.08.017"},{"volume-title":"International journal of remote sensing 37, 21","year":"2016","author":"Ghanea Mohsen","key":"e_1_3_2_1_22_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_23_1","DOI":"10.1109\/AIPR.2017.8457973"},{"unstructured":"Google. 2013. Google Maps\/Google Earth. Google. https:\/\/www.google.com\/permissions\/geoguidelines\/ Google. 2013. Google Maps\/Google Earth. Google. https:\/\/www.google.com\/permissions\/geoguidelines\/","key":"e_1_3_2_1_24_1"},{"doi-asserted-by":"crossref","unstructured":"Bert Guindon. 1997. Computer-based aerial image understanding: A review and assessment of its application to planimetric information extraction from very high resolution satellite images. Canadian journal of remote sensing 23 1 (1997) 38--47. Bert Guindon. 1997. Computer-based aerial image understanding: A review and assessment of its application to planimetric information extraction from very high resolution satellite images. Canadian journal of remote sensing 23 1 (1997) 38--47.","key":"e_1_3_2_1_25_1","DOI":"10.1080\/07038992.1997.10874676"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_26_1","DOI":"10.1109\/MPRV.2008.80"},{"volume-title":"7th European Conference on Synthetic Aperture Radar. VDE, 1--4.","year":"2008","author":"He Wenju","key":"e_1_3_2_1_27_1"},{"doi-asserted-by":"crossref","unstructured":"Jianfeng Huang Xinchang Zhang Qinchuan Xin Ying Sun and Pengcheng Zhang. 2019. Automatic building extraction from high-resolution aerial images and LiDAR data using gated residual refinement network. ISPRS journal of photogrammetry and remote sensing 151 (2019) 91--105. Jianfeng Huang Xinchang Zhang Qinchuan Xin Ying Sun and Pengcheng Zhang. 2019. Automatic building extraction from high-resolution aerial images and LiDAR data using gated residual refinement network. ISPRS journal of photogrammetry and remote sensing 151 (2019) 91--105.","key":"e_1_3_2_1_28_1","DOI":"10.1016\/j.isprsjprs.2019.02.019"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_29_1","DOI":"10.1109\/IGARSS.2016.7729471"},{"doi-asserted-by":"crossref","unstructured":"Andres Huertas and Ramakant Nevatia. 1988. Detecting buildings in aerial images. Computer vision graphics and image processing 41 2 (1988) 131--152. Andres Huertas and Ramakant Nevatia. 1988. Detecting buildings in aerial images. Computer vision graphics and image processing 41 2 (1988) 131--152.","key":"e_1_3_2_1_30_1","DOI":"10.1016\/0734-189X(88)90016-3"},{"unstructured":"ISPRS Working Group II\/4. 2018. ISPRS 2D Semantic Labeling datase. ISPRS. http:\/\/www2.isprs.org\/commissions\/comm3\/wg4\/semanticlabeling.html ISPRS Working Group II\/4. 2018. ISPRS 2D Semantic Labeling datase. ISPRS. http:\/\/www2.isprs.org\/commissions\/comm3\/wg4\/semanticlabeling.html","key":"e_1_3_2_1_31_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_32_1","DOI":"10.1109\/TGRS.2018.2858817"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_33_1","DOI":"10.1080\/01431161.2018.1528024"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_34_1","DOI":"10.1109\/TGRS.2017.2719738"},{"unstructured":"Alex Krizhevsky Ilya Sutskever and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems. NIPS 1097--1105. Alex Krizhevsky Ilya Sutskever and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems. NIPS 1097--1105.","key":"e_1_3_2_1_35_1"},{"doi-asserted-by":"crossref","unstructured":"Steve Lawrence C Lee Giles Ah Chung Tsoi and Andrew D Back. 1997. Face recognition: A convolutional neural-network approach. IEEE transactions on neural networks 8 1 (1997) 98--113. Steve Lawrence C Lee Giles Ah Chung Tsoi and Andrew D Back. 1997. Face recognition: A convolutional neural-network approach. IEEE transactions on neural networks 8 1 (1997) 98--113.","key":"e_1_3_2_1_36_1","DOI":"10.1109\/72.554195"},{"unstructured":"Yann LeCun Yoshua Bengio etal 1995. Convolutional networks for images speech and time series. The handbook of brain theory and neural networks 3361 10 (1995) 1995. Yann LeCun Yoshua Bengio et al. 1995. Convolutional networks for images speech and time series. The handbook of brain theory and neural networks 3361 10 (1995) 1995.","key":"e_1_3_2_1_37_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_38_1","DOI":"10.1109\/5.726791"},{"doi-asserted-by":"crossref","unstructured":"S\u00e9bastien Lef\u00e8vre Jonathan Weber and David Sheeren. 2007. Automatic building extraction in VHR images using advanced morphological operators. In 2007 Urban Remote Sensing Joint Event. IEEE 1--5. S\u00e9bastien Lef\u00e8vre Jonathan Weber and David Sheeren. 2007. Automatic building extraction in VHR images using advanced morphological operators. In 2007 Urban Remote Sensing Joint Event. IEEE 1--5.","key":"e_1_3_2_1_39_1","DOI":"10.1109\/URS.2007.371825"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_40_1","DOI":"10.1109\/TGRS.2015.2400462"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_41_1","DOI":"10.1016\/j.patcog.2017.11.007"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_42_1","DOI":"10.1109\/CVPRW.2018.00043"},{"unstructured":"David Lindenbaum. 2017. Introducing the SpaceNet Road Detection and Routing Challenge and Dataset. https:\/\/medium.com\/the-downlinq\/introducing-the-spacenet-road-detection-and-routing-challenge-and-dataset-7604de39b779. David Lindenbaum. 2017. Introducing the SpaceNet Road Detection and Routing Challenge and Dataset. https:\/\/medium.com\/the-downlinq\/introducing-the-spacenet-road-detection-and-routing-challenge-and-dataset-7604de39b779.","key":"e_1_3_2_1_43_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_44_1","DOI":"10.1109\/CVPR.2015.7298965"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_45_1","DOI":"10.1109\/IGARSS.2017.8127684"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_46_1","DOI":"10.1117\/1.JRS.11.042620"},{"doi-asserted-by":"crossref","unstructured":"Gary Marcus. 2018. Deep learning: A critical appraisal. Gary Marcus. 2018. Deep learning: A critical appraisal.","key":"e_1_3_2_1_47_1","DOI":"10.1155\/2018\/5749479"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_48_1","DOI":"10.1016\/j.isprsjprs.2017.11.009"},{"unstructured":"Volodymyr Mnih. 2013. Machine Learning for Aerial Image Labeling. Ph.D. Dissertation. University of Toronto. Volodymyr Mnih. 2013. Machine Learning for Aerial Image Labeling. Ph.D. Dissertation. University of Toronto.","key":"e_1_3_2_1_49_1"},{"unstructured":"Earth Observatory of Singapore. 2019. Why do urbanisation and deforestation make flooding more likely? Earth Observatory of Singapore. https:\/\/www.earthobservatory.sg\/faq-on-earth-sciences\/why-do-urbanisation-and-deforestation-make-flooding-more-likely Earth Observatory of Singapore. 2019. Why do urbanisation and deforestation make flooding more likely? Earth Observatory of Singapore. https:\/\/www.earthobservatory.sg\/faq-on-earth-sciences\/why-do-urbanisation-and-deforestation-make-flooding-more-likely","key":"e_1_3_2_1_50_1"},{"doi-asserted-by":"crossref","unstructured":"Ali Ozgun Ok. 2013. Automated detection of buildings from single VHR multispectral images using shadow information and graph cuts. ISPRS journal of photogrammetry and remote sensing 86 (2013) 21--40. Ali Ozgun Ok. 2013. Automated detection of buildings from single VHR multispectral images using shadow information and graph cuts. ISPRS journal of photogrammetry and remote sensing 86 (2013) 21--40.","key":"e_1_3_2_1_51_1","DOI":"10.1016\/j.isprsjprs.2013.09.004"},{"unstructured":"OpenStreetMap. 2019. OpenStreetMap Website. OpenStreetMap Foundation. http:\/\/www.openstreetmap.org OpenStreetMap. 2019. OpenStreetMap Website. OpenStreetMap Foundation. http:\/\/www.openstreetmap.org","key":"e_1_3_2_1_52_1"},{"unstructured":"Adam Paszke Sam Gross Soumith Chintala Gregory Chanan Edward Yang Zachary DeVito Zeming Lin Alban Desmaison Luca Antiga and Adam Lerer. 2017. Automatic Differentiation in PyTorch. Adam Paszke Sam Gross Soumith Chintala Gregory Chanan Edward Yang Zachary DeVito Zeming Lin Alban Desmaison Luca Antiga and Adam Lerer. 2017. Automatic Differentiation in PyTorch.","key":"e_1_3_2_1_53_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_54_1","DOI":"10.1016\/j.patrec.2004.09.033"},{"doi-asserted-by":"crossref","unstructured":"Waseem Rawat and Zenghui Wang. 2017. Deep convolutional neural networks for image classification: A comprehensive review. Neural computation 29 9 (2017) 2352--2449. Waseem Rawat and Zenghui Wang. 2017. Deep convolutional neural networks for image classification: A comprehensive review. Neural computation 29 9 (2017) 2352--2449.","key":"e_1_3_2_1_55_1","DOI":"10.1162\/neco_a_00990"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_56_1","DOI":"10.1007\/978-3-319-24574-4_28"},{"volume-title":"Image Processing: Machine Vision Applications VIII","author":"Saito Shunta","key":"e_1_3_2_1_57_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_58_1","DOI":"10.1109\/CVPR.2016.207"},{"unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition.","key":"e_1_3_2_1_59_1"},{"unstructured":"URA Singapore. 2019. Annual Report 2018\/2019. Technical Report. Urban Redevelopment Authority. URA Singapore. 2019. Annual Report 2018\/2019. Technical Report. Urban Redevelopment Authority.","key":"e_1_3_2_1_60_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_61_1","DOI":"10.1109\/LGRS.2012.2193552"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_62_1","DOI":"10.1109\/JSTARS.2014.2308301"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_63_1","DOI":"10.1109\/CVPR.2015.7298594"},{"volume-title":"International journal of applied earth observation and geoinformation 52","year":"2016","author":"Tomljenovic Ivan","key":"e_1_3_2_1_64_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_65_1","DOI":"10.1016\/j.jag.2014.06.016"},{"volume-title":"Annual Report","year":"2018","author":"UNISDR.","key":"e_1_3_2_1_66_1"},{"unstructured":"USGS. 1972. The Landsat Program. U.S. Geological Survey. https:\/\/earthexplorer.usgs.gov\/ USGS. 1972. The Landsat Program. U.S. Geological Survey. https:\/\/earthexplorer.usgs.gov\/","key":"e_1_3_2_1_67_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_68_1","DOI":"10.1109\/IGARSS.2015.7326158"},{"volume-title":"Spacenet: A remote sensing dataset and challenge series.","year":"2018","author":"Etten Adam Van","key":"e_1_3_2_1_69_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_70_1","DOI":"10.1109\/IGARSS.2013.6721129"},{"doi-asserted-by":"crossref","unstructured":"Jan Dirk Wegne Uwe Soergel and Bodo Rosenhahn. 2011. Segment-based building detection with conditional random fields. In 2011 Joint Urban Remote Sensing Event. IEEE 205--208. Jan Dirk Wegne Uwe Soergel and Bodo Rosenhahn. 2011. Segment-based building detection with conditional random fields. In 2011 Joint Urban Remote Sensing Event. IEEE 205--208.","key":"e_1_3_2_1_71_1","DOI":"10.1109\/JURSE.2011.5764756"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_72_1","DOI":"10.3390\/rs10010144"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_73_1","DOI":"10.1109\/JSTARS.2018.2835377"},{"unstructured":"Fisher Yu and Vladlen Koltun. 2015. Multi-scale context aggregation by dilated convolutions. Fisher Yu and Vladlen Koltun. 2015. Multi-scale context aggregation by dilated convolutions.","key":"e_1_3_2_1_74_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_75_1","DOI":"10.3390\/geosciences8050165"},{"unstructured":"J Yuan. 2016. Automatic building extraction in aerial scenes using convolutional networks. J Yuan. 2016. Automatic building extraction in aerial scenes using convolutional networks.","key":"e_1_3_2_1_76_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_77_1","DOI":"10.1109\/IGARSS.2016.7729166"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_78_1","DOI":"10.1109\/CVPR.2017.660"},{"doi-asserted-by":"crossref","unstructured":"W Zhao L Yan Y Chang and L Gong. 2018. High-Resolution Remote Sensing Image Building Extraction Based on Markov Model. 2411--2418 pages. W Zhao L Yan Y Chang and L Gong. 2018. High-Resolution Remote Sensing Image Building Extraction Based on Markov Model. 2411--2418 pages.","key":"e_1_3_2_1_79_1","DOI":"10.5194\/isprs-archives-XLII-3-2411-2018"},{"volume-title":"Asian Conference on Computer Vision. Springer, 291--302","year":"2016","author":"Zuo Tongchun","key":"e_1_3_2_1_80_1"}],"event":{"sponsor":["JKU Johannes Kepler Universit\u00e4t Linz","@WAS International Organization of Information Integration and Web-based Applications and Services"],"acronym":"iiWAS2019","name":"iiWAS2019: The 21st International Conference on Information Integration and Web-based Applications & Services","location":"Munich Germany"},"container-title":["Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3366030.3368456","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3366030.3368456","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:23:51Z","timestamp":1750202631000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3366030.3368456"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,2]]},"references-count":80,"alternative-id":["10.1145\/3366030.3368456","10.1145\/3366030"],"URL":"https:\/\/doi.org\/10.1145\/3366030.3368456","relation":{},"subject":[],"published":{"date-parts":[[2019,12,2]]},"assertion":[{"value":"2020-02-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}