{"id":"https://openalex.org/W2912197073","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633180","title":"Learning Multi-Domain Convolutional Network for RGB-T Visual Tracking","display_name":"Learning Multi-Domain Convolutional Network for RGB-T Visual Tracking","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2912197073","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633180","mag":"2912197073"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2018.8633180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633180","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5052689516","display_name":"Xingming Zhang","orcid":"https://orcid.org/0000-0002-8139-0156"},"institutions":[{"id":"https://openalex.org/I4210151935","display_name":"Dahua Technology (China)","ror":"https://ror.org/04k9ktn61","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210151935"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xingming Zhang","raw_affiliation_strings":["ZHEJIANG DAHUA TECHNOLOGY CO., LTD"],"affiliations":[{"raw_affiliation_string":"ZHEJIANG DAHUA TECHNOLOGY CO., LTD","institution_ids":["https://openalex.org/I4210151935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101862066","display_name":"Xuehan Zhang","orcid":"https://orcid.org/0000-0002-9691-5760"},"institutions":[{"id":"https://openalex.org/I4210151935","display_name":"Dahua Technology (China)","ror":"https://ror.org/04k9ktn61","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210151935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuehan Zhang","raw_affiliation_strings":["ZHEJIANG DAHUA TECHNOLOGY CO., LTD"],"affiliations":[{"raw_affiliation_string":"ZHEJIANG DAHUA TECHNOLOGY CO., LTD","institution_ids":["https://openalex.org/I4210151935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046850003","display_name":"Xuedan Du","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151935","display_name":"Dahua Technology (China)","ror":"https://ror.org/04k9ktn61","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210151935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuedan Du","raw_affiliation_strings":["ZHEJIANG DAHUA TECHNOLOGY CO., LTD"],"affiliations":[{"raw_affiliation_string":"ZHEJIANG DAHUA TECHNOLOGY CO., LTD","institution_ids":["https://openalex.org/I4210151935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110365935","display_name":"Xiangming Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151935","display_name":"Dahua Technology (China)","ror":"https://ror.org/04k9ktn61","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210151935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangming Zhou","raw_affiliation_strings":["ZHEJIANG DAHUA TECHNOLOGY CO., LTD"],"affiliations":[{"raw_affiliation_string":"ZHEJIANG DAHUA TECHNOLOGY CO., LTD","institution_ids":["https://openalex.org/I4210151935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100606500","display_name":"Jun Yin","orcid":"https://orcid.org/0000-0002-8993-3178"},"institutions":[{"id":"https://openalex.org/I4210151935","display_name":"Dahua Technology (China)","ror":"https://ror.org/04k9ktn61","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210151935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Yin","raw_affiliation_strings":["ZHEJIANG DAHUA TECHNOLOGY CO., LTD"],"affiliations":[{"raw_affiliation_string":"ZHEJIANG DAHUA TECHNOLOGY CO., LTD","institution_ids":["https://openalex.org/I4210151935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5052689516"],"corresponding_institution_ids":["https://openalex.org/I4210151935"],"apc_list":null,"apc_paid":null,"fwci":0.8357,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.79617927,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9735000133514404,"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/T11963","display_name":"Impact of Light on Environment and Health","score":0.9724000096321106,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8340798616409302},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7331170439720154},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7072526812553406},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5744880437850952},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5670279264450073},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5639714002609253},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4944133758544922},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.48809942603111267},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46729496121406555},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45755305886268616},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.4327477812767029},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4325825273990631},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.42448586225509644}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8340798616409302},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7331170439720154},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7072526812553406},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5744880437850952},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5670279264450073},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5639714002609253},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4944133758544922},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.48809942603111267},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46729496121406555},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45755305886268616},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.4327477812767029},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4325825273990631},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42448586225509644},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2018.8633180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633180","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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":45,"referenced_works":["https://openalex.org/W161114242","https://openalex.org/W1479814280","https://openalex.org/W1503933356","https://openalex.org/W1686810756","https://openalex.org/W1807914171","https://openalex.org/W1857884451","https://openalex.org/W1964846093","https://openalex.org/W1984914017","https://openalex.org/W1995903777","https://openalex.org/W2016802777","https://openalex.org/W2024307315","https://openalex.org/W2043123015","https://openalex.org/W2091887928","https://openalex.org/W2101488078","https://openalex.org/W2102605133","https://openalex.org/W2106944077","https://openalex.org/W2109579504","https://openalex.org/W2118097920","https://openalex.org/W2121609805","https://openalex.org/W2125614898","https://openalex.org/W2126302311","https://openalex.org/W2136243427","https://openalex.org/W2137097255","https://openalex.org/W2154889144","https://openalex.org/W2159686933","https://openalex.org/W2163605009","https://openalex.org/W2168356304","https://openalex.org/W2179139958","https://openalex.org/W2244956674","https://openalex.org/W2339830253","https://openalex.org/W2343187456","https://openalex.org/W2518013266","https://openalex.org/W2527415613","https://openalex.org/W2557641257","https://openalex.org/W2765667535","https://openalex.org/W2915043960","https://openalex.org/W2963173190","https://openalex.org/W2964253307","https://openalex.org/W3140663364","https://openalex.org/W3143763605","https://openalex.org/W3147165232","https://openalex.org/W6637373629","https://openalex.org/W6676161993","https://openalex.org/W6677907805","https://openalex.org/W6685328683"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W3196371174"],"abstract_inverted_index":{"Object":[0],"tracking":[1,41,53,137,162],"is":[2,79,108,154],"one":[3],"of":[4,11,32,69,86,98,118,146],"the":[5,9,16,21,30,33,76,83,87,105,119,130,134,140,144,160],"challenging":[6],"problems":[7],"in":[8,38,156],"field":[10],"computer":[12],"vision.":[13],"Affected":[14],"by":[15],"unstructured":[17],"environments,":[18],"for":[19,113],"example,":[20],"occlusion,":[22],"noise,":[23],"and":[24,36,90,103,116,129],"light,":[25],"These":[26],"factors":[27],"can":[28],"affect":[29],"appearance":[31],"specific":[34,42],"object":[35],"result":[37],"failures":[39],"when":[40],"objects.":[43],"To":[44],"address":[45],"this":[46,95],"issue,":[47],"we":[48],"propose":[49],"a":[50,64],"novel":[51],"visual":[52,127,136],"method":[54,138,153],"based":[55],"on":[56,125],"multimodal":[57],"convolutional":[58,72],"network":[59,78],"learning.":[60],"Our":[61],"framework":[62],"adopts":[63],"parallel":[65,77],"structure,":[66],"which":[67,149],"consists":[68],"two":[70,96],"shallow":[71],"neural":[73],"networks.":[74],"First,":[75],"used":[80],"to":[81,110],"draw":[82],"different":[84],"features":[85,99],"RGB-T":[88],"(RGB":[89],"thermal)":[91],"data":[92,128],"separately.":[93],"Second,":[94],"kind":[97],"are":[100],"mixed":[101,106],"together":[102],"finally":[104],"feature":[107],"sent":[109],"domain-specific":[111],"layers":[112],"binary":[114],"classification":[115],"identification":[117],"targets.":[120],"We":[121],"perform":[122],"comprehensive":[123],"experiments":[124],"RGBT234":[126],"results":[131],"prove":[132],"that":[133,151],"proposed":[135],"improves":[139],"effects":[141],"significantly":[142],"through":[143],"use":[145],"multi-modal":[147],"features,":[148],"illustrates":[150],"our":[152],"competitive":[155],"performances":[157],"against":[158],"with":[159],"state-of-the-art":[161],"algorithms.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}