{"id":"https://openalex.org/W3008411293","doi":"https://doi.org/10.1145/3376067.3376103","title":"Saliency and Tracking based Semi-supervised Learning for Orbiting Satellite Segmentation","display_name":"Saliency and Tracking based Semi-supervised Learning for Orbiting Satellite Segmentation","publication_year":2019,"publication_date":"2019-12-20","ids":{"openalex":"https://openalex.org/W3008411293","doi":"https://doi.org/10.1145/3376067.3376103","mag":"3008411293"},"language":"en","primary_location":{"id":"doi:10.1145/3376067.3376103","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3376067.3376103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Video and Image Processing","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/A5045184202","display_name":"Peizhuo Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peizhuo Li","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100526684","display_name":"Yunda Sun","orcid":"https://orcid.org/0009-0000-3926-540X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunda Sun","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102796596","display_name":"Xue Wan","orcid":"https://orcid.org/0000-0002-0659-2559"},"institutions":[{"id":"https://openalex.org/I4210086028","display_name":"Technology and Engineering Center for Space Utilization","ror":"https://ror.org/00cn03n83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210086028"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Wan","raw_affiliation_strings":["Technology and Engineering Center for Space Utilization, Chinese, Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Technology and Engineering Center for Space Utilization, Chinese, Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210086028","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5045184202"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.1012,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.48068813,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"90","last_page":"94"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9983999729156494,"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":0.9983999729156494,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9951000213623047,"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":0.9939000010490417,"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/satellite-tracking","display_name":"Satellite tracking","score":0.7146620750427246},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.6995307207107544},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6972774863243103},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6796820163726807},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6626107692718506},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6544867753982544},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6145941615104675},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.41762399673461914},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4145386815071106},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12876003980636597},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12266728281974792},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.0783754289150238}],"concepts":[{"id":"https://openalex.org/C2985889645","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite tracking","level":3,"score":0.7146620750427246},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.6995307207107544},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6972774863243103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6796820163726807},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6626107692718506},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6544867753982544},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6145941615104675},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.41762399673461914},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4145386815071106},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12876003980636597},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12266728281974792},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0783754289150238},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3376067.3376103","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3376067.3376103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Video and Image Processing","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":15,"referenced_works":["https://openalex.org/W590143991","https://openalex.org/W1581087960","https://openalex.org/W1686810756","https://openalex.org/W1875243001","https://openalex.org/W2140557073","https://openalex.org/W2470139095","https://openalex.org/W2557641257","https://openalex.org/W2582761847","https://openalex.org/W2730780157","https://openalex.org/W2963253279","https://openalex.org/W2963299740","https://openalex.org/W2963868681","https://openalex.org/W2963983744","https://openalex.org/W4240153047","https://openalex.org/W4301409532"],"related_works":["https://openalex.org/W3001971600","https://openalex.org/W1522196789","https://openalex.org/W1534189594","https://openalex.org/W642387727","https://openalex.org/W2371910819","https://openalex.org/W1983259426","https://openalex.org/W1973634111","https://openalex.org/W2901336532","https://openalex.org/W1917598433","https://openalex.org/W2575184712"],"abstract_inverted_index":{"The":[0],"trajectory":[1],"and":[2,14,28,38,54,69,76,89,157],"boundary":[3],"of":[4,31,78,103,113],"an":[5],"orbiting":[6],"satellite":[7],"are":[8],"fundamental":[9],"information":[10],"for":[11,59,94],"on-orbit":[12],"repairing":[13],"manipulation":[15],"by":[16,123,139],"space":[17],"robots.":[18],"This":[19],"task,":[20],"however,":[21],"is":[22,142],"challenging":[23],"owing":[24],"to":[25,56,72],"the":[26,34,39,73,79,99,120,134],"freely":[27],"rapidly":[29],"motion":[30],"on-orbiting":[32],"satellites,":[33],"quickly":[35],"varying":[36],"background":[37,156],"sudden":[40],"change":[41],"in":[42,66,154],"illumination":[43,158],"conditions.":[44],"Traditional":[45],"segmentation":[46,100,121],"usually":[47],"relies":[48],"on":[49,144],"a":[50,86,125],"large":[51,74],"annotated":[52,114],"dataset":[53],"needs":[55],"be":[57],"pre-trained":[58],"each":[60],"target,":[61,155],"which":[62,148],"exhausts":[63],"much":[64],"time":[65],"both":[67],"training":[68],"testing":[70],"due":[71],"number":[75],"resolution":[77],"images.":[80],"In":[81],"this":[82],"paper,":[83],"we":[84],"proposed":[85],"STSS":[87],"(Saliency":[88],"Tracking":[90],"based":[91,128],"Semi-supervised":[92],"Learning":[93],"Segmentation)":[95],"algorithm":[96],"that":[97],"provides":[98],"binary":[101],"mask":[102],"target":[104],"satellites":[105],"at":[106],"12":[107],"frames":[108],"per":[109],"second":[110],"without":[111],"requirement":[112],"data.":[115],"Our":[116],"method,":[117],"STSS,":[118],"improves":[119],"performance":[122],"generating":[124],"saliency":[126],"map":[127],"semi-supervised":[129],"on-line":[130],"learning":[131],"approach":[132],"within":[133],"initial":[135],"bounding":[136],"box":[137],"estimated":[138],"tracking.":[140],"Experiment":[141],"evaluated":[143],"our":[145],"generated":[146],"dataset,":[147],"contains":[149],"various":[150],"challenges":[151],"including":[152],"variation":[153],"condition.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
