{"id":"https://openalex.org/W2241051737","doi":"https://doi.org/10.1145/2833258.2833272","title":"An Efficient Framework for Pixel-wise Building Segmentation from Aerial Images","display_name":"An Efficient Framework for Pixel-wise Building Segmentation from Aerial Images","publication_year":2015,"publication_date":"2015-11-18","ids":{"openalex":"https://openalex.org/W2241051737","doi":"https://doi.org/10.1145/2833258.2833272","mag":"2241051737"},"language":"en","primary_location":{"id":"doi:10.1145/2833258.2833272","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2833258.2833272","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixth International Symposium on Information and Communication Technology","raw_type":"proceedings-article"},"type":"conference-paper","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/A5111666601","display_name":"Nguy\u1ec5n Ti\u1ebfn Quang","orcid":null},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Nguyen Tien Quang","raw_affiliation_strings":["Hanoi University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanoi University of Science and Technology","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058684461","display_name":"Nguy\u1ec5n Th\u1ecb Thanh Th\u1ee7y","orcid":"https://orcid.org/0000-0002-9358-6201"},"institutions":[{"id":"https://openalex.org/I4210102522","display_name":"Vietnam National University of Agriculture","ror":"https://ror.org/01abaah21","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210102522"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Nguyen Thi Thuy","raw_affiliation_strings":["Faculty of Information Technology, Vietnam National University of Agriculture"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Vietnam National University of Agriculture","institution_ids":["https://openalex.org/I4210102522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025948040","display_name":"Dinh Viet Sang","orcid":"https://orcid.org/0000-0002-9254-1327"},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Dinh Viet Sang","raw_affiliation_strings":["Hanoi University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanoi University of Science and Technology","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072105691","display_name":"Hu\u1ef3nh Th\u1ecb Thanh B\u00ecnh","orcid":"https://orcid.org/0000-0003-1976-6113"},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Huynh Thi Thanh Binh","raw_affiliation_strings":["Hanoi University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanoi University of Science and Technology","institution_ids":["https://openalex.org/I94518387"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"282","last_page":"287"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994999766349792,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.8454203605651855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7560787200927734},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6836197972297668},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.6028381586074829},{"id":"https://openalex.org/keywords/aerial-imagery","display_name":"Aerial imagery","score":0.5775623917579651},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5684525370597839},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5642330646514893},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5452355742454529},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5218005180358887},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.49765971302986145},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4492744207382202},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4149835705757141},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35147345066070557}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.8454203605651855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7560787200927734},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6836197972297668},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.6028381586074829},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.5775623917579651},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5684525370597839},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5642330646514893},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5452355742454529},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5218005180358887},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.49765971302986145},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4492744207382202},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4149835705757141},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35147345066070557}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2833258.2833272","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2833258.2833272","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixth International Symposium on Information and Communication Technology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6200000047683716,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W150263746","https://openalex.org/W197592383","https://openalex.org/W1510609146","https://openalex.org/W1511986666","https://openalex.org/W1558611393","https://openalex.org/W1573664582","https://openalex.org/W1909515874","https://openalex.org/W1978135836","https://openalex.org/W1991192616","https://openalex.org/W1996749420","https://openalex.org/W2018839022","https://openalex.org/W2021423901","https://openalex.org/W2069842045","https://openalex.org/W2092041043","https://openalex.org/W2099047584","https://openalex.org/W2107732308","https://openalex.org/W2120340025","https://openalex.org/W2123023145","https://openalex.org/W2126747775","https://openalex.org/W2140681449","https://openalex.org/W2141303268","https://openalex.org/W2147880316","https://openalex.org/W2161236525","https://openalex.org/W2168548458","https://openalex.org/W2183208450","https://openalex.org/W2300404176","https://openalex.org/W2315376979","https://openalex.org/W2547241895","https://openalex.org/W2745423625","https://openalex.org/W2886742956","https://openalex.org/W2911964244","https://openalex.org/W3136295810","https://openalex.org/W3140703320","https://openalex.org/W4293052541","https://openalex.org/W4301950487"],"related_works":["https://openalex.org/W3006655138","https://openalex.org/W4283696875","https://openalex.org/W3110585990","https://openalex.org/W4385767632","https://openalex.org/W2898690910","https://openalex.org/W2784132289","https://openalex.org/W4286697184","https://openalex.org/W2889700547","https://openalex.org/W2889866244","https://openalex.org/W3034139063"],"abstract_inverted_index":{"Detection":[0],"of":[1,46,85],"buildings":[2,47],"in":[3,12,72],"aerial":[4,16,60,109],"images":[5],"is":[6],"an":[7,22],"important":[8],"and":[9,15,30,44],"challenging":[10,108],"task":[11],"computer":[13],"vision":[14],"image":[17,61,110],"interpretation.":[18],"This":[19],"paper":[20],"presents":[21],"efficient":[23],"approach":[24],"that":[25],"combines":[26],"Random":[27],"forest":[28],"(RF)":[29],"a":[31,73,107,113,125],"fully":[32,74],"connected":[33,75],"conditional":[34,76],"random":[35,77],"field":[36,78],"(CRF)":[37],"on":[38,58,106],"various":[39],"features":[40],"for":[41,80,90],"the":[42,94],"detection":[43],"segmentation":[45],"at":[48],"pixel":[49],"level.":[50],"RF":[51,68],"allows":[52],"one":[53],"to":[54],"learn":[55],"extremely":[56],"fast":[57],"big":[59],"data.":[62],"The":[63,83],"unary":[64],"potentials":[65,92],"given":[66],"by":[67],"are":[69],"then":[70],"combined":[71],"model":[79],"pixel-wise":[81],"classification.":[82],"use":[84],"high":[86,99],"dimensional":[87],"Gaussian":[88],"filter":[89],"pairwise":[91],"makes":[93],"inference":[95],"tractable":[96],"while":[97],"obtaining":[98],"classification":[100],"accuracy.":[101],"Experiments":[102],"have":[103],"been":[104],"conducted":[105],"dataset":[111],"from":[112],"recent":[114],"ISPRS":[115],"Semantic":[116],"Labeling":[117],"Contest":[118],"[9].":[119],"We":[120],"obtained":[121],"state-of-the-art":[122],"accuracy":[123],"with":[124],"reasonable":[126],"computation":[127],"time.":[128]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}