{"id":"https://openalex.org/W2986380337","doi":"https://doi.org/10.1109/igarss.2019.8897989","title":"A Weakly-Supervised Deep Network for DSM-Aided Vehicle Detection","display_name":"A Weakly-Supervised Deep Network for DSM-Aided Vehicle Detection","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2986380337","doi":"https://doi.org/10.1109/igarss.2019.8897989","mag":"2986380337"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8897989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8897989","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","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/A5100761149","display_name":"Xin Wu","orcid":"https://orcid.org/0000-0002-1733-3560"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Wu","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology (BIT), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology (BIT), Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075013625","display_name":"Danfeng Hong","orcid":"https://orcid.org/0000-0002-3212-9584"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Danfeng Hong","raw_affiliation_strings":["Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083368958","display_name":"Jiaojiao Tian","orcid":"https://orcid.org/0000-0002-8407-5098"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jiaojiao Tian","raw_affiliation_strings":["Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090334584","display_name":"Ralph Kiefl","orcid":"https://orcid.org/0000-0001-7622-5458"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ralph Kiefl","raw_affiliation_strings":["German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067803447","display_name":"Ran Tao","orcid":"https://orcid.org/0000-0002-5243-7189"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Tao","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology (BIT), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology (BIT), Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3051,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.61860897,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"96","issue":null,"first_page":"1318","last_page":"1321"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9984999895095825,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.994700014591217,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7494718432426453},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7078707218170166},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.698724091053009},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.678228497505188},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.5721604824066162},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4438367486000061},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4400601089000702},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4082903563976288},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37188437581062317},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3339277505874634},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.0822691023349762}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7494718432426453},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7078707218170166},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.698724091053009},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.678228497505188},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.5721604824066162},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4438367486000061},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4400601089000702},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4082903563976288},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37188437581062317},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3339277505874634},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0822691023349762},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2019.8897989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8897989","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:elib.dlr.de:130573","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8897989>.","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1673310716","https://openalex.org/W1786486465","https://openalex.org/W2035875937","https://openalex.org/W2118246710","https://openalex.org/W2194775991","https://openalex.org/W2308318555","https://openalex.org/W2588117332","https://openalex.org/W2609880332","https://openalex.org/W2755992512","https://openalex.org/W2885785305","https://openalex.org/W2897962879","https://openalex.org/W2902746003","https://openalex.org/W2903688779","https://openalex.org/W2904086561","https://openalex.org/W2907147407","https://openalex.org/W2924927660","https://openalex.org/W2939570633","https://openalex.org/W2950800384","https://openalex.org/W2953303055","https://openalex.org/W2962749812","https://openalex.org/W3101012758","https://openalex.org/W3101640299","https://openalex.org/W3103294617","https://openalex.org/W3105021316","https://openalex.org/W6637131181","https://openalex.org/W6714138976"],"related_works":["https://openalex.org/W2733535455","https://openalex.org/W2789436332","https://openalex.org/W2921357635","https://openalex.org/W2804356489","https://openalex.org/W2789609993","https://openalex.org/W2028104478","https://openalex.org/W3206555449","https://openalex.org/W3130226347","https://openalex.org/W3088358344","https://openalex.org/W3206899727","https://openalex.org/W3113331579","https://openalex.org/W3203350115","https://openalex.org/W2411392023","https://openalex.org/W2909102496","https://openalex.org/W2787614951","https://openalex.org/W3041014620","https://openalex.org/W2613985965","https://openalex.org/W3028160911","https://openalex.org/W2926837263","https://openalex.org/W3048487290"],"abstract_inverted_index":{"With":[0],"the":[1,4,13,17,54,91,98,112],"breakthrough":[2],"of":[3,7,20,102],"spatial":[5],"resolution":[6],"optical":[8],"remote":[9,32],"sensing":[10,33],"images":[11],"at":[12],"sub-meter":[14],"level":[15,42],"and":[16,47,58,85,122],"explosive":[18],"development":[19],"deep":[21,68],"learning,":[22],"geospatial":[23,74],"object":[24,41,75],"detection":[25,76,117],"has":[26],"achieved":[27],"a":[28,66,79,86,103],"growing":[29],"interest":[30],"in":[31,40],"community.":[34],"However,":[35],"labeling":[36],"large":[37,104],"training":[38],"datasets":[39],"is":[43,71],"still":[44],"an":[45],"expensive":[46],"tedious":[48],"procedure.":[49],"This":[50],"might":[51],"lead":[52],"to":[53,109],"poor":[55],"model":[56,82],"generalization":[57],"degraded":[59],"network":[60,69,88],"learning":[61],"ability.":[62],"To":[63],"this":[64],"end,":[65],"weakly-supervised":[67],"(WSDN)":[70],"developed":[72],"for":[73],"by":[77],"applying":[78],"digital":[80],"surface":[81],"(DSM)-aided":[83],"auto-labeling":[84],"pre-trained":[87],"learned":[89],"from":[90],"task-independent":[92],"dataset.":[93],"Experimental":[94],"results":[95],"conducted":[96],"on":[97],"stereo":[99],"aerial":[100],"imagery":[101],"camping":[105],"site":[106],"are":[107],"performed":[108],"demonstrate":[110],"that":[111],"proposed":[113],"WSDN":[114],"yields":[115],"better":[116],"results,":[118],"with":[119],"62.78%":[120],"precision":[121],"55.13%":[123],"recall.":[124]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
