{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T14:16:53Z","timestamp":1776003413134,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":23,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,11,5]],"date-time":"2019-11-05T00:00:00Z","timestamp":1572912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CCF-1740761, RI-1815697, CCF-1733798, CCF-1618247"],"award-info":[{"award-number":["CCF-1740761, RI-1815697, CCF-1733798, CCF-1618247"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,11,5]]},"DOI":"10.1145\/3347146.3359348","type":"proceedings-article","created":{"date-parts":[[2019,11,13]],"date-time":"2019-11-13T22:08:16Z","timestamp":1573682896000},"page":"520-523","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Road Network Reconstruction from satellite images with Machine Learning Supported by Topological Methods"],"prefix":"10.1145","author":[{"given":"Tamal K.","family":"Dey","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, The Ohio State University, Columbus, Ohio"}]},{"given":"Jiayuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, The Ohio State University, Columbus, Ohio"}]},{"given":"Yusu","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, The Ohio State University, Columbus, Ohio"}]}],"member":"320","published-online":{"date-parts":[[2019,11,5]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"A. Buslaev. 2018. Spacenet round 3 winner. https:\/\/github.com\/SpaceNetChallenge\/RoadDetector\/tree\/master\/albu-solution. (2018).  A. Buslaev. 2018. Spacenet round 3 winner. https:\/\/github.com\/SpaceNetChallenge\/RoadDetector\/tree\/master\/albu-solution. (2018)."},{"key":"e_1_3_2_1_2_1","volume-title":"The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.","author":"Buslaev A.","unstructured":"A. Buslaev , S. Seferbekov , V. Iglovikov , and A. Shvets . 2018. Fully convolutional network for automatic road extraction from satellite imagery . In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. A. Buslaev, S. Seferbekov, V. Iglovikov, and A. Shvets. 2018. Fully convolutional network for automatic road extraction from satellite imagery. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops."},{"key":"e_1_3_2_1_3_1","unstructured":"D. Ciresan A. Giusti L. M. Gambardella and J. Schmidhuber. 2012. Deep neural networks segment neuronal membranes in electron microscopy images. In Advances in neural information processing systems. 2843--2851.  D. Ciresan A. Giusti L. M. Gambardella and J. Schmidhuber. 2012. Deep neural networks segment neuronal membranes in electron microscopy images. In Advances in neural information processing systems. 2843--2851."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"S. Das TT Mirnalinee and K. Varghese. 2011. Use of salient features for the design of a multistage framework to extract roads from high-resolution multispectral satellite images. IEEE transactions on Geoscience and Remote sensing 49 10 (2011) 3906--3931.  S. Das TT Mirnalinee and K. Varghese. 2011. Use of salient features for the design of a multistage framework to extract roads from high-resolution multispectral satellite images. IEEE transactions on Geoscience and Remote sensing 49 10 (2011) 3906--3931.","DOI":"10.1109\/TGRS.2011.2136381"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2346172"},{"key":"e_1_3_2_1_6_1","volume-title":"Proc. 25th ACM SIGSPATIAL. ACM, 58","author":"Dey T. K.","unstructured":"T. K. Dey , J. Wang , and Y. Wang . 2017. Improved road network reconstruction using discrete morse theory . In Proc. 25th ACM SIGSPATIAL. ACM, 58 . T. K. Dey, J. Wang, and Y. Wang. 2017. Improved road network reconstruction using discrete morse theory. In Proc. 25th ACM SIGSPATIAL. ACM, 58."},{"key":"e_1_3_2_1_7_1","first-page":"1","article-title":"Graph Reconstruction by Discrete Morse Theory. In Proc. 34th","volume":"31","author":"Dey T. K.","year":"2018","unstructured":"T. K. Dey , J. Wang , and Y. Wang . 2018 . Graph Reconstruction by Discrete Morse Theory. In Proc. 34th Sympos. Comput. Geom. 31 : 1 -- 31 :15. T. K. Dey, J. Wang, and Y. Wang. 2018. Graph Reconstruction by Discrete Morse Theory. In Proc. 34th Sympos. Comput. Geom. 31:1--31:15.","journal-title":"Sympos. Comput. Geom."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"T. K. Dey J. Wang and Y. Wang. 2019. Road Network Reconstruction from satellite images with Machine Learning Supported by Topological Methods. arXiv preprint arXiv:1909.06728 (2019).  T. K. Dey J. Wang and Y. Wang. 2019. Road Network Reconstruction from satellite images with Machine Learning Supported by Topological Methods. arXiv preprint arXiv:1909.06728 (2019).","DOI":"10.1145\/3347146.3359348"},{"key":"e_1_3_2_1_9_1","unstructured":"H. Edelsbrunner and J. Harer. 2010. Computational Topology: an Introduction. American Mathematical Society. I-XII 1--241 pages.  H. Edelsbrunner and J. Harer. 2010. Computational Topology: an Introduction. American Mathematical Society. I-XII 1--241 pages."},{"key":"e_1_3_2_1_10_1","volume-title":"Morse theory for cell complexes. Advances in mathematics 134, 1","author":"Forman R.","year":"1998","unstructured":"R. Forman . 1998. Morse theory for cell complexes. Advances in mathematics 134, 1 ( 1998 ), 90--145. R. Forman. 1998. Morse theory for cell complexes. Advances in mathematics 134, 1 (1998), 90--145."},{"key":"e_1_3_2_1_11_1","volume-title":"Proc. 23rd ACM SIGSPATIAL. ACM, 69","author":"Gu X.","unstructured":"X. Gu , A. Zang , X. Huang , A. Tokuta , and X. Chen . 2015. Fusion of color images and LiDAR data for lane classification . In Proc. 23rd ACM SIGSPATIAL. ACM, 69 . X. Gu, A. Zang, X. Huang, A. Tokuta, and X. Chen. 2015. Fusion of color images and LiDAR data for lane classification. In Proc. 23rd ACM SIGSPATIAL. ACM, 69."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2007.70552"},{"key":"e_1_3_2_1_13_1","volume-title":"Proc. of the IEEE conference on computer vision and pattern recognition. 770--778","author":"He K.","unstructured":"K. He , X. Zhang , S. Ren , and J. Sun . 2016. Deep residual learning for image recognition . In Proc. of the IEEE conference on computer vision and pattern recognition. 770--778 . K. He, X. Zhang, S. Ren, and J. Sun. 2016. Deep residual learning for image recognition. In Proc. of the IEEE conference on computer vision and pattern recognition. 770--778."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.95"},{"key":"e_1_3_2_1_15_1","volume-title":"U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention","author":"Ronneberger O.","year":"2015","unstructured":"O. Ronneberger , P. Fischer , and T. Brox . 2015 . U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention . Springer , 234--241. O. Ronneberger, P. Fischer, and T. Brox. 2015. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention. Springer, 234--241."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2013.2272593"},{"key":"e_1_3_2_1_17_1","volume-title":"The persistent cosmic web and its filamentary structure - I. Theory and implementation. 414 (June","author":"Sousbie T.","year":"2011","unstructured":"T. Sousbie . 2011. The persistent cosmic web and its filamentary structure - I. Theory and implementation. 414 (June 2011 ), 350--383. arXiv:astro-ph.CO\/1009.4015 T. Sousbie. 2011. The persistent cosmic web and its filamentary structure - I. Theory and implementation. 414 (June 2011), 350--383. arXiv:astro-ph.CO\/1009.4015"},{"key":"e_1_3_2_1_18_1","volume-title":"Proc. of the 2nd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery. ACM, 29--32","author":"Sun T.","unstructured":"T. Sun , Z. Di , and Y. Wang . 2018. Combining Satellite Imagery and GPS Data for Road Extraction . In Proc. of the 2nd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery. ACM, 29--32 . T. Sun, Z. Di, and Y. Wang. 2018. Combining Satellite Imagery and GPS Data for Road Extraction. In Proc. of the 2nd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery. ACM, 29--32."},{"key":"e_1_3_2_1_19_1","unstructured":"A. Van Etten D. Lindenbaum and T. M. Bacastow. 2018. SpaceNet: A Remote Sensing Dataset and Challenge Series. arXiv preprint arXiv:1807.01232 (2018).  A. Van Etten D. Lindenbaum and T. M. Bacastow. 2018. SpaceNet: A Remote Sensing Dataset and Challenge Series. arXiv preprint arXiv:1807.01232 (2018)."},{"key":"e_1_3_2_1_20_1","volume-title":"Proc. 23rd ACM SIGSPATIAL. ACM, 25","author":"Wang S.","unstructured":"S. Wang , Y. Wang , and Y. Li . 2015. Efficient map reconstruction and augmentation via topological methods . In Proc. 23rd ACM SIGSPATIAL. ACM, 25 . S. Wang, Y. Wang, and Y. Li. 2015. Efficient map reconstruction and augmentation via topological methods. In Proc. 23rd ACM SIGSPATIAL. ACM, 25."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.12123"},{"key":"e_1_3_2_1_22_1","volume-title":"Proc. of the 1st ACM SIGSPATIAL Workshop on High-Precision Maps and Intelligent Applications for Autonomous Vehicles. ACM, 1.","author":"Zang A.","unstructured":"A. Zang , R. Xu , Z. Li , and D. Doria . 2017. Lane boundary extraction from satellite imagery . In Proc. of the 1st ACM SIGSPATIAL Workshop on High-Precision Maps and Intelligent Applications for Autonomous Vehicles. ACM, 1. A. Zang, R. Xu, Z. Li, and D. Doria. 2017. Lane boundary extraction from satellite imagery. In Proc. of the 1st ACM SIGSPATIAL Workshop on High-Precision Maps and Intelligent Applications for Autonomous Vehicles. ACM, 1."},{"key":"e_1_3_2_1_23_1","volume-title":"IEEE Conf. on Computer Vision and Pattern Recognition (CVPR). 2881--2890","author":"Zhao H.","unstructured":"H. Zhao , J. Shi , X. Qi , X. Wang , and J. Jia . 2017. Pyramid scene parsing network . In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR). 2881--2890 . H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia. 2017. Pyramid scene parsing network. In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR). 2881--2890."}],"event":{"name":"SIGSPATIAL '19: 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","location":"Chicago IL USA","acronym":"SIGSPATIAL '19","sponsor":["SIGSPATIAL ACM Special Interest Group on Spatial Information"]},"container-title":["Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3347146.3359348","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3347146.3359348","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3347146.3359348","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:44:28Z","timestamp":1750203868000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3347146.3359348"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,5]]},"references-count":23,"alternative-id":["10.1145\/3347146.3359348","10.1145\/3347146"],"URL":"https:\/\/doi.org\/10.1145\/3347146.3359348","relation":{},"subject":[],"published":{"date-parts":[[2019,11,5]]},"assertion":[{"value":"2019-11-05","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}