{"id":"https://openalex.org/W3090937333","doi":"https://doi.org/10.1109/icip40778.2020.9191353","title":"Deep Learning Based Cross-Spectral Disparity Estimation For Stereo Imaging","display_name":"Deep Learning Based Cross-Spectral Disparity Estimation For Stereo Imaging","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3090937333","doi":"https://doi.org/10.1109/icip40778.2020.9191353","mag":"3090937333"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191353","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191353","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","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/A5052676758","display_name":"Nils Genser","orcid":"https://orcid.org/0000-0002-8564-2541"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Nils Genser","raw_affiliation_strings":["Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042665477","display_name":"Andreas Spruck","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Spruck","raw_affiliation_strings":["Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101633542","display_name":"J\u00fcrgen Seiler","orcid":"https://orcid.org/0000-0002-3016-110X"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jurgen Seiler","raw_affiliation_strings":["Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062850220","display_name":"Andr\u00e9 Kaup","orcid":"https://orcid.org/0000-0002-0929-5074"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andre Kaup","raw_affiliation_strings":["Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Multimedia Communications and Signal Processing, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4895,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.66553037,"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":"2536","last_page":"2540"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9988999962806702,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9988999962806702,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.735323429107666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.735124409198761},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6024907827377319},{"id":"https://openalex.org/keywords/stereo-camera","display_name":"Stereo camera","score":0.5057339668273926},{"id":"https://openalex.org/keywords/spectral-density-estimation","display_name":"Spectral density estimation","score":0.4583723843097687},{"id":"https://openalex.org/keywords/narrowband","display_name":"Narrowband","score":0.452421098947525},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.413334459066391},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1702614426612854},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.08973893523216248}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.735323429107666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.735124409198761},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6024907827377319},{"id":"https://openalex.org/C185078393","wikidata":"https://www.wikidata.org/wiki/Q313783","display_name":"Stereo camera","level":2,"score":0.5057339668273926},{"id":"https://openalex.org/C30049272","wikidata":"https://www.wikidata.org/wiki/Q6555326","display_name":"Spectral density estimation","level":3,"score":0.4583723843097687},{"id":"https://openalex.org/C2776096036","wikidata":"https://www.wikidata.org/wiki/Q1140483","display_name":"Narrowband","level":2,"score":0.452421098947525},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.413334459066391},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1702614426612854},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.08973893523216248},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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:10.1109/icip40778.2020.9191353","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191353","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W63091017","https://openalex.org/W2087408688","https://openalex.org/W2104974755","https://openalex.org/W2109168054","https://openalex.org/W2144041313","https://openalex.org/W2165114467","https://openalex.org/W2259424905","https://openalex.org/W2604231069","https://openalex.org/W2608890887","https://openalex.org/W2762808238","https://openalex.org/W2771026831","https://openalex.org/W2789250882","https://openalex.org/W2796625543","https://openalex.org/W2890640381","https://openalex.org/W2902562967","https://openalex.org/W2904094572","https://openalex.org/W2952825894","https://openalex.org/W2963619659","https://openalex.org/W2971354864","https://openalex.org/W3100388886","https://openalex.org/W3148370606","https://openalex.org/W4234282793"],"related_works":["https://openalex.org/W3123462798","https://openalex.org/W1606028226","https://openalex.org/W2145652935","https://openalex.org/W2010500171","https://openalex.org/W1974522807","https://openalex.org/W1584634440","https://openalex.org/W400202667","https://openalex.org/W1967673162","https://openalex.org/W1965444921","https://openalex.org/W2769734079"],"abstract_inverted_index":{"Recently,":[0],"cross-spectral":[1,33,49,129],"stereo-camera":[2],"setups":[3],"found":[4],"their":[5],"way":[6],"from":[7,76],"special":[8],"applications":[9],"to":[10,28,71,83,134],"mass":[11],"market,":[12],"especially":[13],"in":[14],"smartphones,":[15],"automotive":[16],"systems,":[17],"or":[18,52],"drones.":[19],"In":[20,89,132],"the":[21,92,137],"following,":[22],"a":[23,60,67,111,127,145],"novel":[24],"concept":[25],"is":[26,56,69,101,120,140],"introduced":[27],"bring":[29],"stereo":[30,41,80],"cameras":[31],"and":[32,82],"disparity":[34],"estimation":[35,93],"together.":[36],"So":[37],"far,":[38],"either":[39],"monomodal":[40],"algorithms":[42],"exist":[43],"that":[44,58],"are":[45],"not":[46],"suitable":[47],"for":[48,110],"image":[50],"registration,":[51],"structural":[53],"template":[54],"matching":[55],"applied":[57],"achieves":[59],"low":[61],"quality.":[62],"To":[63],"overcome":[64],"these":[65],"limitations,":[66],"technique":[68],"proposed":[70],"synthesize":[72],"arbitrary":[73],"spectral":[74,95],"components":[75],"widely":[77],"available":[78],"color":[79],"databases,":[81],"retrain":[84],"mono-modal":[85],"deep":[86],"learning":[87],"methods.":[88],"this":[90],"contribution,":[91],"of":[94,114,147],"bands":[96],"based":[97],"on":[98,141],"random":[99],"processes":[100],"shown":[102],"together":[103],"with":[104],"noise":[105],"models,":[106],"which":[107],"also":[108],"allow":[109],"robust":[112],"registration":[113],"narrowband":[115],"components.":[116],"The":[117],"theoretical":[118],"examination":[119],"completed":[121],"by":[122,144],"an":[123],"extensive":[124],"evaluation,":[125],"including":[126],"self-manufactured":[128],"camera":[130],"setup.":[131],"comparison":[133],"state-of-the-art":[135],"techniques,":[136],"end-point":[138],"error":[139],"average":[142],"reduced":[143],"factor":[146],"seven.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}