{"id":"https://openalex.org/W4411171694","doi":"https://doi.org/10.1109/access.2025.3578292","title":"Image Coding for Object Recognition Tasks Based on Contour Feature Learning With Flexible Object Selection","display_name":"Image Coding for Object Recognition Tasks Based on Contour Feature Learning With Flexible Object Selection","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411171694","doi":"https://doi.org/10.1109/access.2025.3578292"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3578292","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3578292","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3578292","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003035267","display_name":"Takahiro Shindo","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takahiro Shindo","raw_affiliation_strings":["Graduate School of Fundamental Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan","Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0009-0003-9202-4594","affiliations":[{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053367139","display_name":"Taiju Watanabe","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Taiju Watanabe","raw_affiliation_strings":["Graduate School of Fundamental Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan","Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0009-0000-5325-3253","affiliations":[{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102674043","display_name":"Yui Tatsumi","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yui Tatsumi","raw_affiliation_strings":["School of Fundamental Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan","School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0009-0009-6073-1829","affiliations":[{"raw_affiliation_string":"School of Fundamental Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hiroshi Watanabe","orcid":"https://orcid.org/0000-0002-9306-688X"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Watanabe","raw_affiliation_strings":["Graduate School of Fundamental Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan","Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-9306-688X","affiliations":[{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5003035267"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.0875,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7812932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"13","issue":null,"first_page":"106606","last_page":"106617"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9810000061988831,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9810000061988831,"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/T13579","display_name":"Image and Video Stabilization","score":0.9682999849319458,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9460999965667725,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7756439447402954},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7312126755714417},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.6154294013977051},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6035749912261963},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.6031281352043152},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5721011757850647},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5171167850494385},{"id":"https://openalex.org/keywords/3d-single-object-recognition","display_name":"3D single-object recognition","score":0.48219242691993713},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4485968351364136},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.42146044969558716},{"id":"https://openalex.org/keywords/deep-sky-object","display_name":"Deep-sky object","score":0.41789889335632324},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24626454710960388},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11447528004646301}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7756439447402954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7312126755714417},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.6154294013977051},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6035749912261963},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6031281352043152},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5721011757850647},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5171167850494385},{"id":"https://openalex.org/C14551309","wikidata":"https://www.wikidata.org/wiki/Q4636325","display_name":"3D single-object recognition","level":4,"score":0.48219242691993713},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4485968351364136},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.42146044969558716},{"id":"https://openalex.org/C201276399","wikidata":"https://www.wikidata.org/wiki/Q249389","display_name":"Deep-sky object","level":3,"score":0.41789889335632324},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24626454710960388},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11447528004646301},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3578292","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3578292","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d14ab3a47b4b48b4b40ecf119a98fc0a","is_oa":true,"landing_page_url":"https://doaj.org/article/d14ab3a47b4b48b4b40ecf119a98fc0a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 106606-106617 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3578292","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3578292","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5942591708","display_name":null,"funder_award_id":"JPJ012368C05101","funder_id":"https://openalex.org/F4320335839","funder_display_name":"National Institute of Information and Communications Technology"}],"funders":[{"id":"https://openalex.org/F4320335839","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2029098067","https://openalex.org/W2064076387","https://openalex.org/W2140196014","https://openalex.org/W2170023599","https://openalex.org/W2963150697","https://openalex.org/W2963661664","https://openalex.org/W2963770864","https://openalex.org/W2971904947","https://openalex.org/W3030801383","https://openalex.org/W3034469748","https://openalex.org/W3046869848","https://openalex.org/W3082548248","https://openalex.org/W3113550930","https://openalex.org/W3138516171","https://openalex.org/W3160555381","https://openalex.org/W3160673571","https://openalex.org/W3160882100","https://openalex.org/W3169876831","https://openalex.org/W3186910762","https://openalex.org/W3209814877","https://openalex.org/W4284691924","https://openalex.org/W4285217780","https://openalex.org/W4288325606","https://openalex.org/W4289821645","https://openalex.org/W4312365925","https://openalex.org/W4372260482","https://openalex.org/W4376464601","https://openalex.org/W4386075611","https://openalex.org/W4388187175","https://openalex.org/W4389252700","https://openalex.org/W4389474451","https://openalex.org/W4390874575","https://openalex.org/W4391306523","https://openalex.org/W4391307027","https://openalex.org/W4391974577","https://openalex.org/W4392931027","https://openalex.org/W4392980423","https://openalex.org/W4395069551","https://openalex.org/W4400070421","https://openalex.org/W4402915458","https://openalex.org/W4404295367","https://openalex.org/W4404295444","https://openalex.org/W4404612908","https://openalex.org/W6747701344","https://openalex.org/W6754634825","https://openalex.org/W6755207826","https://openalex.org/W6852412637","https://openalex.org/W6861232000","https://openalex.org/W6873900500","https://openalex.org/W6893711219"],"related_works":["https://openalex.org/W4362565474","https://openalex.org/W2019233926","https://openalex.org/W1510094335","https://openalex.org/W20667011","https://openalex.org/W1991200873","https://openalex.org/W2048782450","https://openalex.org/W2094492355","https://openalex.org/W2297673025","https://openalex.org/W3212154412","https://openalex.org/W1999285768"],"abstract_inverted_index":{"The":[0],"consumption":[1],"of":[2,15,150,239],"image":[3,16,25,105,108,119,124,153,157,199],"data":[4],"by":[5,90,195,243],"machines":[6],"is":[7,52,98],"rapidly":[8],"increasing":[9],"due":[10],"to":[11,72,83,93,100,129,172,227],"the":[12,94,111,151,235],"growing":[13],"adoption":[14],"recognition":[17,125,143,161,205,221],"technologies.":[18],"This":[19,32],"trend":[20],"has":[21,42],"accelerated":[22],"research":[23],"in":[24,46,133],"compression":[26,158,200],"techniques":[27],"tailored":[28],"for":[29,39,57,116,160,204],"machine":[30],"processing.":[31],"emerging":[33],"field,":[34],"known":[35],"as":[36,55,136,178],"Image":[37],"Coding":[38],"Machines":[40],"(ICM),":[41],"gained":[43],"significant":[44],"attention":[45],"recent":[47],"years.":[48],"In":[49,188],"particular,":[50],"ICM":[51,170],"increasingly":[53],"seen":[54],"essential":[56],"collaborative":[58],"systems":[59,174],"between":[60],"edge":[61,75,84,183,228],"devices":[62,184],"and":[63,107,118,138,185,202,237],"cloud":[64,77],"AI.":[65],"Since":[66],"large":[67],"AI":[68,78,97],"models":[69,126,144],"are":[70,80,127],"challenging":[71],"deploy":[73],"on":[74,182,210],"devices,":[76],"services":[79],"made":[81],"available":[82],"users,":[85],"who":[86],"can":[87,162],"utilize":[88],"them":[89,245],"transmitting":[91],"images":[92,215],"cloud.":[95],"Cloud":[96],"expected":[99],"handle":[101],"various":[102,220],"tasks,":[103],"including":[104],"generation":[106],"recognition,":[109],"with":[110,219,246],"latter":[112],"being":[113],"especially":[114],"valuable":[115],"video":[117],"analysis.":[120],"Given":[121],"its":[122],"utility,":[123],"anticipated":[128],"replace":[130],"human":[131],"analysts":[132],"applications":[134],"such":[135,177],"farm":[137],"traffic":[139],"monitoring.":[140],"Moreover,":[141],"since":[142],"require":[145],"only":[146],"a":[147],"small":[148],"fraction":[149],"total":[152],"data,":[154],"developing":[155],"specialized":[156],"methods":[159,171,208,242],"significantly":[163],"enhance":[164],"communication":[165],"efficiency.":[166],"However,":[167],"applying":[168],"conventional":[169,247],"edge-cloud":[173],"presents":[175],"challenges,":[176],"increased":[179],"computational":[180,225],"load":[181],"limited":[186],"versatility.":[187],"this":[189],"paper,":[190],"we":[191,233],"address":[192],"these":[193],"challenges":[194],"proposing":[196],"two":[197],"novel":[198],"methods\u2014SA-ICM":[201],"ST-ICM\u2014designed":[203],"models.":[206],"These":[207],"focus":[209],"preserving":[211],"object":[212],"contours":[213],"within":[214],"while":[216],"maintaining":[217],"compatibility":[218],"models,":[222],"without":[223],"adding":[224],"overhead":[226],"devices.":[229],"Through":[230],"experimental":[231],"evaluations,":[232],"demonstrate":[234],"versatility":[236],"effectiveness":[238],"our":[240],"proposed":[241],"comparing":[244],"approaches.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
