{"id":"https://openalex.org/W2901550124","doi":"https://doi.org/10.1145/3274895.3274993","title":"Fusion of aerial lidar and images for road segmentation with deep CNN","display_name":"Fusion of aerial lidar and images for road segmentation with deep CNN","publication_year":2018,"publication_date":"2018-11-06","ids":{"openalex":"https://openalex.org/W2901550124","doi":"https://doi.org/10.1145/3274895.3274993","mag":"2901550124"},"language":"en","primary_location":{"id":"doi:10.1145/3274895.3274993","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3274895.3274993","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","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/A5063529706","display_name":"Biswas Parajuli","orcid":null},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Biswas Parajuli","raw_affiliation_strings":["Florida State University"],"affiliations":[{"raw_affiliation_string":"Florida State University","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101585285","display_name":"Piyush Kumar","orcid":"https://orcid.org/0000-0002-7912-393X"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Piyush Kumar","raw_affiliation_strings":["Florida State University"],"affiliations":[{"raw_affiliation_string":"Florida State University","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047462138","display_name":"Tathagata Mukherjee","orcid":"https://orcid.org/0000-0001-8753-5718"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tathagata Mukherjee","raw_affiliation_strings":["Intelligent Robotics"],"affiliations":[{"raw_affiliation_string":"Intelligent Robotics","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054940160","display_name":"Eduardo L. Pasiliao","orcid":"https://orcid.org/0000-0002-6403-6649"},"institutions":[{"id":"https://openalex.org/I1280414376","display_name":"United States Air Force Research Laboratory","ror":"https://ror.org/02e2egq70","country_code":"US","type":"facility","lineage":["https://openalex.org/I1280414376","https://openalex.org/I1330347796","https://openalex.org/I4210102105","https://openalex.org/I4389425425"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eduardo Pasiliao","raw_affiliation_strings":["Air Force Research Laboratory"],"affiliations":[{"raw_affiliation_string":"Air Force Research Laboratory","institution_ids":["https://openalex.org/I1280414376"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012995283","display_name":"Sachin Jambawalikar","orcid":"https://orcid.org/0000-0003-1839-6798"},"institutions":[{"id":"https://openalex.org/I2799503643","display_name":"Columbia University Irving Medical Center","ror":"https://ror.org/01esghr10","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I2799503643"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sachin Jambawalikar","raw_affiliation_strings":["Columbia University Medical Center"],"affiliations":[{"raw_affiliation_string":"Columbia University Medical Center","institution_ids":["https://openalex.org/I2799503643"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5063529706"],"corresponding_institution_ids":["https://openalex.org/I103163165"],"apc_list":null,"apc_paid":null,"fwci":0.913,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.73086137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"548","last_page":"551"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9944999814033508,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.8714901804924011},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7307929992675781},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6873676776885986},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6826514005661011},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6673227548599243},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6452081203460693},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6188953518867493},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5879590511322021},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.47896721959114075},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.47730696201324463},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.46930813789367676},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.4381547272205353},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.42882663011550903},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.4258206784725189},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.24322634935379028},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15958362817764282},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08179670572280884}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8714901804924011},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7307929992675781},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6873676776885986},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6826514005661011},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6673227548599243},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6452081203460693},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6188953518867493},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5879590511322021},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.47896721959114075},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.47730696201324463},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.46930813789367676},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.4381547272205353},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.42882663011550903},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.4258206784725189},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.24322634935379028},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15958362817764282},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08179670572280884},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3274895.3274993","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3274895.3274993","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W73112891","https://openalex.org/W1903029394","https://openalex.org/W1984288883","https://openalex.org/W2067912884","https://openalex.org/W2081294768","https://openalex.org/W2113207845","https://openalex.org/W2139427956","https://openalex.org/W2155893237","https://openalex.org/W2184188583","https://openalex.org/W2412782625","https://openalex.org/W2587989515","https://openalex.org/W2593886839","https://openalex.org/W2618742129","https://openalex.org/W2780861787","https://openalex.org/W2798925380","https://openalex.org/W2951713345","https://openalex.org/W2963881378","https://openalex.org/W2963956866","https://openalex.org/W4299828299"],"related_works":["https://openalex.org/W4384112194","https://openalex.org/W2783354812","https://openalex.org/W2103009189","https://openalex.org/W4312958259","https://openalex.org/W4390813131","https://openalex.org/W2349383066","https://openalex.org/W4308259661","https://openalex.org/W4328132048","https://openalex.org/W2594043982","https://openalex.org/W3036493597"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"attempt":[4],"to":[5,18,31],"fuse":[6],"both":[7],"airborne":[8],"Lidar":[9,71,79],"and":[10,42,63,80],"high":[11],"resolution":[12],"images":[13],"(0.5":[14],"feet":[15],"per":[16],"pixel)":[17],"identify":[19],"road":[20,36,100],"networks":[21],"in":[22,45],"a":[23,46,52,84],"large":[24],"geographic":[25],"region.":[26],"We":[27,73,82,112],"perform":[28],"pixel-wise":[29],"segmentation":[30,101],"classify":[32],"each":[33],"pixel":[34],"as":[35,118,120],"or":[37],"non-road":[38],"based":[39],"on":[40,114],"color":[41,61],"depth":[43,65],"features":[44],"larger":[47],"neighborhood":[48],"context.":[49],"This":[50],"constitutes":[51],"bimodal":[53],"setting":[54],"because":[55],"the":[56,60,64,98,104,107],"RGB":[57,109],"pixels":[58],"represent":[59],"space":[62],"values":[66],"come":[67],"from":[68],"three":[69],"dimensional":[70],"readings.":[72],"present":[74],"multiple":[75],"strategies":[76],"for":[77,97,124],"fusing":[78],"images.":[81],"describe":[83],"cost-effective,":[85],"modular,":[86],"deep":[87],"convolution":[88],"network":[89],"design,":[90],"TriSeg":[91],"which":[92],"gives":[93],"better":[94],"IoU":[95],"metric":[96],"aerial":[99],"problem":[102],"than":[103],"state":[105],"of":[106],"art":[108],"only":[110],"architectures.":[111],"report":[113],"many":[115],"other":[116],"architectures":[117],"well":[119],"release":[121],"our":[122],"dataset":[123],"further":[125],"research:":[126],"https://bitbucket.org/biswas/fusion_lidar_images.":[127]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}