{"id":"https://openalex.org/W3206448148","doi":"https://doi.org/10.1109/icra48506.2021.9561681","title":"Collaborative Learning of Multiple-Discontinuous-Image Saliency Prediction for Drone Exploration","display_name":"Collaborative Learning of Multiple-Discontinuous-Image Saliency Prediction for Drone Exploration","publication_year":2021,"publication_date":"2021-05-30","ids":{"openalex":"https://openalex.org/W3206448148","doi":"https://doi.org/10.1109/icra48506.2021.9561681","mag":"3206448148"},"language":"en","primary_location":{"id":"doi:10.1109/icra48506.2021.9561681","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9561681","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5089494443","display_name":"Ting-Tsan Chu","orcid":null},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ting-Tsan Chu","raw_affiliation_strings":["National Yang Ming Chiao Tung University,Department of Computer Science,Hsinchu,Taiwan,300"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University,Department of Computer Science,Hsinchu,Taiwan,300","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101849108","display_name":"Po-Heng Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Po-Heng Chen","raw_affiliation_strings":["National Yang Ming Chiao Tung University,Department of Computer Science,Hsinchu,Taiwan,300"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University,Department of Computer Science,Hsinchu,Taiwan,300","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024460451","display_name":"Pinjie Huang","orcid":"https://orcid.org/0000-0001-7909-9901"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Pin-Jie Huang","raw_affiliation_strings":["National Yang Ming Chiao Tung University,Department of Computer Science,Hsinchu,Taiwan,300"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University,Department of Computer Science,Hsinchu,Taiwan,300","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101426057","display_name":"Kuan\u2010Wen Chen","orcid":"https://orcid.org/0000-0002-4159-201X"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Kuan-Wen Chen","raw_affiliation_strings":["National Yang Ming Chiao Tung University,Department of Computer Science,Hsinchu,Taiwan,300"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University,Department of Computer Science,Hsinchu,Taiwan,300","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I148366613"],"apc_list":null,"apc_paid":null,"fwci":0.191,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51877994,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"11343","last_page":"11349"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","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/T11605","display_name":"Visual Attention and Saliency Detection","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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9882000088691711,"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"}},{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9825999736785889,"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/drone","display_name":"Drone","score":0.8959435224533081},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7224745750427246},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6444897651672363},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5208631157875061},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4581533670425415},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38767293095588684}],"concepts":[{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.8959435224533081},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7224745750427246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6444897651672363},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5208631157875061},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4581533670425415},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38767293095588684},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48506.2021.9561681","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9561681","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309618","display_name":"Ministry of Science and Technology","ror":"https://ror.org/02b207r52"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1510835000","https://openalex.org/W1686810756","https://openalex.org/W1831674524","https://openalex.org/W1934890906","https://openalex.org/W1946606198","https://openalex.org/W1997741316","https://openalex.org/W2040253108","https://openalex.org/W2078903912","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2121947860","https://openalex.org/W2128272608","https://openalex.org/W2163605009","https://openalex.org/W2164084182","https://openalex.org/W2194775991","https://openalex.org/W2212216676","https://openalex.org/W2528092473","https://openalex.org/W2558906385","https://openalex.org/W2583180462","https://openalex.org/W2612135493","https://openalex.org/W2732026016","https://openalex.org/W2738450183","https://openalex.org/W2755981968","https://openalex.org/W2758187654","https://openalex.org/W2788239209","https://openalex.org/W2798665861","https://openalex.org/W2889942734","https://openalex.org/W2890258603","https://openalex.org/W2902009049","https://openalex.org/W2910850106","https://openalex.org/W2911147127","https://openalex.org/W2955060956","https://openalex.org/W2962716998","https://openalex.org/W2963169347","https://openalex.org/W2963503775","https://openalex.org/W2963581854","https://openalex.org/W2963828885","https://openalex.org/W2964114039","https://openalex.org/W2964145162","https://openalex.org/W3005401190","https://openalex.org/W3035666869","https://openalex.org/W3097096317","https://openalex.org/W3099561715","https://openalex.org/W3101840568","https://openalex.org/W3122238731","https://openalex.org/W6637373629","https://openalex.org/W6638807622","https://openalex.org/W6684191040","https://openalex.org/W6725404246","https://openalex.org/W6732940373","https://openalex.org/W6744291110","https://openalex.org/W6744446066","https://openalex.org/W6758488825"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W2058170566","https://openalex.org/W4306674287","https://openalex.org/W2772917594","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747"],"abstract_inverted_index":{"Most":[0],"of":[1,111,138,143,183],"the":[2,43,104,109,116,144,164],"existing":[3,123,145],"saliency":[4,24,47,63,75,95,100,110,124,148,173,186],"prediction":[5,25,48,125,174,187],"research":[6],"focuses":[7],"on":[8],"either":[9],"single":[10],"images":[11,18,34,52,87,142],"or":[12,39],"videos":[13],"(or":[14],"more":[15],"precisely":[16],"multiple":[17,33,50,129],"in":[19],"sequence).":[20],"However,":[21],"to":[22,26,31,41,45,150,181],"apply":[23],"drone":[27],"exploration":[28],"that":[29,97,163,182],"has":[30],"consider":[32],"from":[35,140],"different":[36],"view":[37],"angles":[38],"localizations":[40],"determine":[42],"direction":[44],"explore,":[46],"over":[49],"discontinuous":[51,130],"is":[53],"required.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58,132],"propose":[59],"a":[60,73,90,135],"deep":[61],"relative":[62,99,117],"model":[64],"(MS-Net)":[65],"for":[66,79,155],"such":[67,128],"an":[68],"application.":[69],"MS-Net":[70],"starts":[71],"with":[72,127,189],"single-image":[74,170],"feature":[76],"extraction":[77],"network":[78],"each":[80,112],"image":[81,113,147,185],"separately":[82],"and":[83,158,171,176],"then":[84],"integrate":[85],"these":[86],"by":[88,114],"using":[89],"GCN-based":[91],"mechanism":[92],"called":[93],"multi-image":[94],"fusion":[96],"learns":[98],"information":[101],"among":[102],"all":[103],"images.":[105],"Finally,":[106],"it":[107],"predicts":[108],"considering":[115],"information.":[118],"Because":[119],"there":[120],"are":[121],"no":[122],"datasets":[126,149],"images,":[131],"randomly":[133],"cropped":[134],"large":[136],"number":[137],"sub-images":[139],"360°":[141,146,184],"build":[151],"our":[152],"own":[153],"dataset":[154],"both":[156,169],"training":[157],"evaluation.":[159],"Experimental":[160],"results":[161],"showed":[162],"proposed":[165],"MSNet":[166],"considerably":[167],"outperformed":[168],"video":[172],"methods":[175],"could":[177],"achieve":[178],"comparative":[179],"performance":[180],"even":[188],"only":[190],"limited":[191],"field-of-views,":[192],"i.e.,":[193],"five":[194],"sub-images,":[195],"considered.":[196]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}