{"id":"https://openalex.org/W3123922547","doi":"https://doi.org/10.3390/rs13020274","title":"Matching Large Baseline Oblique Stereo Images Using an End-to-End Convolutional Neural Network","display_name":"Matching Large Baseline Oblique Stereo Images Using an End-to-End Convolutional Neural Network","publication_year":2021,"publication_date":"2021-01-14","ids":{"openalex":"https://openalex.org/W3123922547","doi":"https://doi.org/10.3390/rs13020274","mag":"3123922547"},"language":"en","primary_location":{"id":"doi:10.3390/rs13020274","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13020274","pdf_url":"https://www.mdpi.com/2072-4292/13/2/274/pdf?version=1610691574","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/13/2/274/pdf?version=1610691574","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032045601","display_name":"Guobiao Yao","orcid":"https://orcid.org/0000-0001-6305-4514"},"institutions":[{"id":"https://openalex.org/I44445938","display_name":"Shandong Jianzhu University","ror":"https://ror.org/01gbfax37","country_code":"CN","type":"education","lineage":["https://openalex.org/I44445938"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guobiao Yao","raw_affiliation_strings":["School of Surveying and Geo-Informatics, Shandong Jianzhu University, No. 1000 Fengming Road, Jinan 250101, China"],"affiliations":[{"raw_affiliation_string":"School of Surveying and Geo-Informatics, Shandong Jianzhu University, No. 1000 Fengming Road, Jinan 250101, China","institution_ids":["https://openalex.org/I44445938"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008672128","display_name":"Alper Y\u0131lmaz","orcid":"https://orcid.org/0000-0003-0755-2628"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alper Yilmaz","raw_affiliation_strings":["Photogrammetric Computer Vision Lab, The Ohio State University, Columbus, OH 43210, USA"],"affiliations":[{"raw_affiliation_string":"Photogrammetric Computer Vision Lab, The Ohio State University, Columbus, OH 43210, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100425448","display_name":"Li Zhang","orcid":"https://orcid.org/0000-0001-7914-0679"},"institutions":[{"id":"https://openalex.org/I4210114963","display_name":"Chinese Academy of Surveying and Mapping","ror":"https://ror.org/02j693n47","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114963"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhang","raw_affiliation_strings":["Chinese Academy of Surveying & Mapping, No. 28 Lianhuachi West Road, Beijing 100830, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Surveying & Mapping, No. 28 Lianhuachi West Road, Beijing 100830, China","institution_ids":["https://openalex.org/I4210114963"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100608836","display_name":"Fei Meng","orcid":"https://orcid.org/0000-0003-0192-3870"},"institutions":[{"id":"https://openalex.org/I44445938","display_name":"Shandong Jianzhu University","ror":"https://ror.org/01gbfax37","country_code":"CN","type":"education","lineage":["https://openalex.org/I44445938"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Meng","raw_affiliation_strings":["School of Surveying and Geo-Informatics, Shandong Jianzhu University, No. 1000 Fengming Road, Jinan 250101, China"],"affiliations":[{"raw_affiliation_string":"School of Surveying and Geo-Informatics, Shandong Jianzhu University, No. 1000 Fengming Road, Jinan 250101, China","institution_ids":["https://openalex.org/I44445938"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002755226","display_name":"Haibin Ai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114963","display_name":"Chinese Academy of Surveying and Mapping","ror":"https://ror.org/02j693n47","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114963"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haibin Ai","raw_affiliation_strings":["Chinese Academy of Surveying & Mapping, No. 28 Lianhuachi West Road, Beijing 100830, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Surveying & Mapping, No. 28 Lianhuachi West Road, Beijing 100830, China","institution_ids":["https://openalex.org/I4210114963"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101649502","display_name":"Fengxiang Jin","orcid":"https://orcid.org/0000-0003-3444-5326"},"institutions":[{"id":"https://openalex.org/I44445938","display_name":"Shandong Jianzhu University","ror":"https://ror.org/01gbfax37","country_code":"CN","type":"education","lineage":["https://openalex.org/I44445938"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengxiang Jin","raw_affiliation_strings":["School of Surveying and Geo-Informatics, Shandong Jianzhu University, No. 1000 Fengming Road, Jinan 250101, China"],"affiliations":[{"raw_affiliation_string":"School of Surveying and Geo-Informatics, Shandong Jianzhu University, No. 1000 Fengming Road, Jinan 250101, China","institution_ids":["https://openalex.org/I44445938"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5032045601"],"corresponding_institution_ids":["https://openalex.org/I44445938"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.4566,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.83677723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"13","issue":"2","first_page":"274","last_page":"274"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T10531","display_name":"Advanced Vision and Imaging","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7173281311988831},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.6803880929946899},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6437315940856934},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5688167810440063},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.468948096036911},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.43835312128067017},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.368949294090271},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27839529514312744},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0896044671535492}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7173281311988831},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.6803880929946899},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6437315940856934},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5688167810440063},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.468948096036911},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.43835312128067017},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.368949294090271},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27839529514312744},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0896044671535492},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs13020274","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13020274","pdf_url":"https://www.mdpi.com/2072-4292/13/2/274/pdf?version=1610691574","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c5f1ec5cc0564689bb9bb278ead7580e","is_oa":true,"landing_page_url":"https://doaj.org/article/c5f1ec5cc0564689bb9bb278ead7580e","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 13, Iss 2, p 274 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/13/2/274/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs13020274","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs13020274","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13020274","pdf_url":"https://www.mdpi.com/2072-4292/13/2/274/pdf?version=1610691574","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/10"},{"display_name":"Peace, Justice and strong institutions","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2696157397","display_name":null,"funder_award_id":"ZR201","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4274852942","display_name":null,"funder_award_id":"41601489","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6809183074","display_name":null,"funder_award_id":"Project No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G95219373","display_name":null,"funder_award_id":"ZR2015DQ007","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3123922547.pdf","grobid_xml":"https://content.openalex.org/works/W3123922547.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1533955188","https://openalex.org/W1612997784","https://openalex.org/W1929856797","https://openalex.org/W1971661558","https://openalex.org/W1980911747","https://openalex.org/W2052094314","https://openalex.org/W2098789800","https://openalex.org/W2115072079","https://openalex.org/W2119605622","https://openalex.org/W2124404372","https://openalex.org/W2126060993","https://openalex.org/W2148179360","https://openalex.org/W2151103935","https://openalex.org/W2152235937","https://openalex.org/W2172188317","https://openalex.org/W2177274842","https://openalex.org/W2263386426","https://openalex.org/W2320444803","https://openalex.org/W2345643369","https://openalex.org/W2559871160","https://openalex.org/W2618039218","https://openalex.org/W2737260104","https://openalex.org/W2749224737","https://openalex.org/W2884088147","https://openalex.org/W2884354140","https://openalex.org/W2898538166","https://openalex.org/W2948182274","https://openalex.org/W2950600620","https://openalex.org/W2963059198","https://openalex.org/W2963235042","https://openalex.org/W2963775347","https://openalex.org/W2965729937","https://openalex.org/W2969192308","https://openalex.org/W2969574023","https://openalex.org/W2973665503","https://openalex.org/W2981799316","https://openalex.org/W2989650831","https://openalex.org/W3010242131","https://openalex.org/W3043075211","https://openalex.org/W3092233714","https://openalex.org/W3103648783","https://openalex.org/W3105885503","https://openalex.org/W6692704047","https://openalex.org/W6704545620","https://openalex.org/W6752208963","https://openalex.org/W6756040250","https://openalex.org/W6763111990","https://openalex.org/W6766367136"],"related_works":["https://openalex.org/W2038416447","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W2364151838","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2066926363","https://openalex.org/W2947043951"],"abstract_inverted_index":{"The":[0,214],"available":[1],"stereo":[2,20,176],"matching":[3,52,151,168,200],"algorithms":[4],"produce":[5,14,235],"large":[6,23],"number":[7],"of":[8,156,190,208,217],"false":[9],"positive":[10],"matches":[11,157],"or":[12],"only":[13],"a":[15,47,72],"few":[16],"true-positives":[17],"across":[18,38],"oblique":[19,175],"images":[21,177],"with":[22,54,122,128,241],"baseline.":[24],"This":[25],"undesired":[26],"result":[27],"happens":[28],"due":[29],"to":[30,79,82],"the":[31,39,94,109,138,145,150,154,161,188,191,203,232],"complex":[32],"perspective":[33],"deformation":[34],"and":[35,70,116,153,182,194,211,230],"radiometric":[36],"distortion":[37],"images.":[40],"To":[41,92],"address":[42],"this":[43,136,218],"problem,":[44],"we":[45,68,77,99],"propose":[46],"novel":[48],"affine":[49,74,84,237],"invariant":[50,85,238],"feature":[51],"algorithm":[53,201],"subpixel":[55],"accuracy":[56,155],"based":[57,107,165],"on":[58,108,172],"an":[59,101],"end-to-end":[60],"convolutional":[61],"neural":[62],"network":[63,132],"(CNN).":[64],"In":[65],"our":[66,129,199,222],"method,":[67],"adopt":[69],"modify":[71],"Hessian":[73,86],"network,":[75],"which":[76],"refer":[78],"as":[80,149],"IHesAffNet,":[81],"obtain":[83],"regions":[87],"using":[88,112,144],"deep":[89,119,162],"learning":[90,163],"framework.":[91],"improve":[93],"correlation":[95],"between":[96],"corresponding":[97,239],"features,":[98],"introduce":[100],"empirical":[102],"weighted":[103],"loss":[104],"function":[105],"(EWLF)":[106],"negative":[110],"samples":[111],"K":[113],"nearest":[114],"neighbors,":[115],"then":[117],"generate":[118,226],"learning-based":[120],"descriptors":[121],"high":[123,227],"discrimination":[124],"that":[125,198],"is":[126],"realized":[127],"multiple":[130],"hard":[131],"structure":[133],"(MTHardNets).":[134],"Following":[135],"step,":[137],"conjugate":[139],"features":[140,240],"are":[141,158],"produced":[142],"by":[143,179],"Euclidean":[146],"distance":[147],"ratio":[148],"metric,":[152],"optimized":[159],"through":[160],"transform":[164,243],"least":[166],"square":[167],"(DLT-LSM).":[169],"Finally,":[170],"experiments":[171],"Large":[173],"baseline":[174],"acquired":[178],"ground":[180],"close-range":[181],"unmanned":[183],"aerial":[184],"vehicle":[185],"(UAV)":[186],"verify":[187],"effectiveness":[189],"proposed":[192,223],"approach,":[193],"comprehensive":[195],"comparisons":[196],"demonstrate":[197],"outperforms":[202],"state-of-art":[204],"methods":[205],"in":[206],"terms":[207],"accuracy,":[209],"distribution":[210],"correct":[212],"ratio.":[213],"main":[215],"contributions":[216],"article":[219],"are:":[220],"(i)":[221],"MTHardNets":[224],"can":[225,234],"quality":[228],"descriptors;":[229],"(ii)":[231],"IHesAffNet":[233],"substantial":[236],"reliable":[242],"parameters.":[244]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}