{"id":"https://openalex.org/W4312530542","doi":"https://doi.org/10.1145/3565291.3565330","title":"EMN: An Edge Mask based Network for Building Detection from Remote Sensing Images","display_name":"EMN: An Edge Mask based Network for Building Detection from Remote Sensing Images","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4312530542","doi":"https://doi.org/10.1145/3565291.3565330"},"language":"en","primary_location":{"id":"doi:10.1145/3565291.3565330","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3565291.3565330","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Big Data Technologies","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036667949","display_name":"Qiu Lu","orcid":"https://orcid.org/0000-0001-5563-851X"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiu Lu","raw_affiliation_strings":["University of Jinan, China"],"affiliations":[{"raw_affiliation_string":"University of Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114038068","display_name":"Wen Ji Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Ji Dong","raw_affiliation_strings":["University of Jinan, China"],"affiliations":[{"raw_affiliation_string":"University of Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054500885","display_name":"Yan Dong","orcid":"https://orcid.org/0000-0003-3752-226X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan Dong","raw_affiliation_strings":["Surveying and Mapping Institute of Shandong Province, China"],"affiliations":[{"raw_affiliation_string":"Surveying and Mapping Institute of Shandong Province, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100684243","display_name":"Tao Xu","orcid":"https://orcid.org/0000-0002-4409-3777"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Xu","raw_affiliation_strings":["University of Jinan, China"],"affiliations":[{"raw_affiliation_string":"University of Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050996016","display_name":"Zhen Liu","orcid":"https://orcid.org/0000-0001-7887-868X"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Liu","raw_affiliation_strings":["University of Jinan, China"],"affiliations":[{"raw_affiliation_string":"University of Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110951499","display_name":"Jie Qing Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Qing Liu","raw_affiliation_strings":["Beihang University, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5036667949"],"corresponding_institution_ids":["https://openalex.org/I34949971"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21821528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"242","last_page":"247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7228939533233643},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6991934180259705},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6249294877052307},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5478042960166931},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5397075414657593},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5186969041824341},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.49493569135665894},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3738602101802826},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20483168959617615},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.17732298374176025}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7228939533233643},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6991934180259705},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6249294877052307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5478042960166931},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5397075414657593},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5186969041824341},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.49493569135665894},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3738602101802826},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20483168959617615},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.17732298374176025},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3565291.3565330","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3565291.3565330","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Big Data Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.8500000238418579,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W2102605133","https://openalex.org/W2109255472","https://openalex.org/W2549139847","https://openalex.org/W2565639579","https://openalex.org/W2613718673","https://openalex.org/W2901712839","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2992240579","https://openalex.org/W3006674459","https://openalex.org/W3148703355","https://openalex.org/W3172752666","https://openalex.org/W3179888767","https://openalex.org/W3184439416","https://openalex.org/W3209989670","https://openalex.org/W6746568730","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2038862184","https://openalex.org/W2039365229","https://openalex.org/W2028049428","https://openalex.org/W2101902114","https://openalex.org/W2145843506","https://openalex.org/W2379089757","https://openalex.org/W4249592067","https://openalex.org/W2056407677","https://openalex.org/W2358781543","https://openalex.org/W4293054829"],"abstract_inverted_index":{"Building":[0],"detection":[1,26,63],"from":[2,85],"remote":[3],"sensing":[4],"images":[5],"plays":[6],"an":[7,91],"important":[8],"role":[9],"in":[10,68],"applications":[11],"such":[12],"as":[13],"urban":[14],"management":[15],"and":[16,31,48,60],"city":[17],"planning.":[18],"In":[19],"recent":[20],"years,":[21],"deep":[22],"learning":[23],"basic":[24],"building":[25,50,57,62],"methods":[27,34,64],"have":[28,74],"become":[29],"popular,":[30],"many":[32],"sophisticated":[33],"are":[35,65],"proposed":[36,106],"with":[37],"expectation":[38],"of":[39],"replacing":[40],"tedious":[41],"human":[42],"labeling":[43],"process.":[44],"However,":[45],"complex":[46,86],"backgrounds":[47],"diverse":[49],"appearance":[51],"impose":[52],"great":[53],"challenges":[54],"to":[55,81],"the":[56,69,105],"detection.":[58],"Automatic":[59],"accurate":[61],"on":[66],"demand":[67],"community.":[70],"Considering":[71],"that":[72,104],"buildings":[73],"distinct":[75],"edge":[76,92],"features,":[77],"which":[78],"enables":[79],"them":[80],"be":[82],"well":[83],"distinguished":[84],"backgrounds,":[87],"this":[88],"paper":[89],"proposes":[90],"mask-based":[93],"enhancement":[94],"network":[95],"(EMN)":[96],"for":[97],"boosting":[98],"Faster":[99],"R-CNN.":[100],"Our":[101],"experiments":[102],"show":[103],"method":[107],"demonstrates":[108],"its":[109],"effectiveness.":[110]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}