{"id":"https://openalex.org/W3004400191","doi":"https://doi.org/10.1117/12.2558414","title":"Optical-to-SAR image registration using a combination of CNN descriptors and cross-correlation coefficient","display_name":"Optical-to-SAR image registration using a combination of CNN descriptors and cross-correlation coefficient","publication_year":2020,"publication_date":"2020-01-31","ids":{"openalex":"https://openalex.org/W3004400191","doi":"https://doi.org/10.1117/12.2558414","mag":"3004400191"},"language":"en","primary_location":{"id":"doi:10.1117/12.2558414","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2558414","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Twelfth International Conference on Machine Vision (ICMV 2019)","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/A5097788736","display_name":"Shabanov Akhmedkhan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210107660","display_name":"Institute for Information Transmission Problems","ror":"https://ror.org/013w2d378","country_code":"RU","type":"facility","lineage":["https://openalex.org/I1313323035","https://openalex.org/I4210097085","https://openalex.org/I4210107660"]}],"countries":["RU"],"is_corresponding":true,"raw_author_name":"Shabanov Akhmedkhan","raw_affiliation_strings":["Institute for Information Transmission Problems (Kharkevich Institute) (Russian Federation)"],"affiliations":[{"raw_affiliation_string":"Institute for Information Transmission Problems (Kharkevich Institute) (Russian Federation)","institution_ids":["https://openalex.org/I4210107660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052179283","display_name":"Sergey Gladilin","orcid":"https://orcid.org/0000-0003-2425-207X"},"institutions":[{"id":"https://openalex.org/I4210107660","display_name":"Institute for Information Transmission Problems","ror":"https://ror.org/013w2d378","country_code":"RU","type":"facility","lineage":["https://openalex.org/I1313323035","https://openalex.org/I4210097085","https://openalex.org/I4210107660"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Sergey Gladilin","raw_affiliation_strings":["Institute for Information Transmission Problems (Kharkevich Institute) (Russian Federation)"],"affiliations":[{"raw_affiliation_string":"Institute for Information Transmission Problems (Kharkevich Institute) (Russian Federation)","institution_ids":["https://openalex.org/I4210107660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015956798","display_name":"Evgeny Shvets","orcid":null},"institutions":[{"id":"https://openalex.org/I4210107660","display_name":"Institute for Information Transmission Problems","ror":"https://ror.org/013w2d378","country_code":"RU","type":"facility","lineage":["https://openalex.org/I1313323035","https://openalex.org/I4210097085","https://openalex.org/I4210107660"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Evgeny A. Shvets","raw_affiliation_strings":["Institute for Information Transmission Problems (Kharkevich Institute) (Russian Federation)"],"affiliations":[{"raw_affiliation_string":"Institute for Information Transmission Problems (Kharkevich Institute) (Russian Federation)","institution_ids":["https://openalex.org/I4210107660"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5097788736"],"corresponding_institution_ids":["https://openalex.org/I4210107660"],"apc_list":null,"apc_paid":null,"fwci":0.2931,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.53994421,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"63","last_page":"63"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.883899986743927,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.883899986743927,"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":0.8334000110626221,"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"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.8152999877929688,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.704961895942688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6976779103279114},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.6744700074195862},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5918768644332886},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5132553577423096},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4764293134212494},{"id":"https://openalex.org/keywords/cross-correlation","display_name":"Cross-correlation","score":0.4705890715122223},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46052321791648865},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.4356391429901123},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.39967113733291626},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20854529738426208},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19168514013290405},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.08006167411804199}],"concepts":[{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.704961895942688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6976779103279114},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.6744700074195862},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5918768644332886},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5132553577423096},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4764293134212494},{"id":"https://openalex.org/C163018871","wikidata":"https://www.wikidata.org/wiki/Q1302587","display_name":"Cross-correlation","level":2,"score":0.4705890715122223},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46052321791648865},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.4356391429901123},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39967113733291626},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20854529738426208},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19168514013290405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.08006167411804199},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2558414","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2558414","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Twelfth International Conference on Machine Vision (ICMV 2019)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2372194214","https://openalex.org/W3081640970","https://openalex.org/W4200439127","https://openalex.org/W2021013714","https://openalex.org/W2412250669","https://openalex.org/W2359856669","https://openalex.org/W1488551807","https://openalex.org/W2023979854","https://openalex.org/W2560331580","https://openalex.org/W4253009869"],"abstract_inverted_index":{"Image":[0],"registration":[1,29,45,114,132,146],"is":[2,73,156],"a":[3,202,218],"problem":[4],"of":[5,11,41,54,86,98,110,129,134,169],"aligning":[6],"two":[7],"or":[8,15],"more":[9],"images":[10,20,55,85],"the":[12,42,52,64,80,107,126,159,167,192],"same":[13],"scene":[14],"object.":[16],"The":[17],"case":[18,128],"when":[19],"are":[21,56,100,152],"taken":[22],"using":[23,115],"different":[24,87],"sensors":[25],"-":[26,30,133,177],"multimodal":[27,66,130],"image":[28,44,113,131],"has":[31],"applications":[32],"in":[33],"medical":[34],"imaging":[35],"and":[36,103,118,136,174,181,205,213],"remote":[37],"sensing.":[38],"Unfortunately,":[39],"many":[40],"existing":[43],"methods":[46,93,176],"operate":[47],"under":[48],"crude":[49],"assumptions":[50],"(i.e.,":[51],"intensities":[53],"linearly":[57],"correlated),":[58],"which":[59],"makes":[60],"them":[61,99],"inapplicable":[62],"for":[63,196],"accurate":[65],"registration.":[67],"One":[68],"approach":[69],"to":[70,74,78],"this":[71,122,163],"task":[72],"use":[75,143],"deep":[76,91],"learning":[77,92],"capture":[79],"complex":[81],"intensity":[82],"dependencies":[83],"between":[84],"modalities.":[88],"However,":[89],"while":[90],"produce":[94],"good":[95],"results,":[96],"most":[97],"trained":[101],"end-to-end":[102,215],"do":[104],"not":[105],"utilize":[106],"accumulated":[108],"body":[109],"knowledge":[111],"about":[112],"\u201cclassic\u201d":[116,211],"information-theoretic":[117],"statistical":[119],"methods.":[120],"In":[121],"paper":[123],"we":[124,165,200],"consider":[125],"specific":[127],"optical":[135],"synthetic":[137],"aperture":[138],"radar":[139],"(SAR)":[140],"images.":[141],"We":[142,183],"classic":[144,193],"feature-based":[145],"pipeline":[147],"(first,":[148],"corresponding":[149],"feature":[150,171],"points":[151],"found,":[153],"then":[154],"RANSAC":[155],"used":[157],"as":[158],"transform":[160],"estimator).":[161],"Within":[162],"method":[164,195,204,212],"compare":[166],"effectiveness":[168],"various":[170],"point":[172],"detection":[173],"correspondence":[175],"both":[178,210],"neural":[179],"network-based":[180],"traditional.":[182],"find":[184],"that":[185,207],"Siamese":[186],"network":[187,216],"outperforms":[188,209],"(but":[189],"only":[190],"slightly)":[191],"cross-entropy-based":[194],"finding":[197],"correspondences.":[198],"Finally,":[199],"propose":[201],"hybrid":[203],"show":[206],"it":[208],"an":[214],"by":[217],"significant":[219],"margin.":[220]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}