{"id":"https://openalex.org/W4410665743","doi":"https://doi.org/10.1145/3736771","title":"Traditional Patterns Segmentation Algorithm Based on Memory Learning Model","display_name":"Traditional Patterns Segmentation Algorithm Based on Memory Learning Model","publication_year":2025,"publication_date":"2025-05-23","ids":{"openalex":"https://openalex.org/W4410665743","doi":"https://doi.org/10.1145/3736771"},"language":"en","primary_location":{"id":"doi:10.1145/3736771","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3736771","pdf_url":null,"source":{"id":"https://openalex.org/S4210184050","display_name":"Journal on Computing and Cultural Heritage","issn_l":"1556-4673","issn":["1556-4673","1556-4711"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal on Computing and Cultural Heritage","raw_type":"journal-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/A5015262364","display_name":"Haiying Zhao","orcid":"https://orcid.org/0000-0002-0240-4573"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiying Zhao","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0240-4573","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044457303","display_name":"Yan Wang","orcid":"https://orcid.org/0000-0002-3248-3284"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Wang","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3248-3284","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101712512","display_name":"Kun Xu","orcid":"https://orcid.org/0000-0001-6677-3215"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Xu","raw_affiliation_strings":["State Key Laboratory of Information Photonics and Optical Communications, Beijing University of\u00a0Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6677-3215","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Photonics and Optical Communications, Beijing University of\u00a0Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102220008","display_name":"Zhan Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhan Gao","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0004-9283-8210","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100703776","display_name":"Yue Zhou","orcid":"https://orcid.org/0009-0001-4523-0008"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Zhou","raw_affiliation_strings":["State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-4523-0008","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08512655,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"3","first_page":"1","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9940000176429749,"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":0.9940000176429749,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/segmentation","display_name":"Segmentation","score":0.6353251934051514},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6081998348236084},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5542369484901428},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4198395907878876},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3947766423225403},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35712602734565735}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6353251934051514},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6081998348236084},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5542369484901428},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4198395907878876},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3947766423225403},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35712602734565735}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3736771","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3736771","pdf_url":null,"source":{"id":"https://openalex.org/S4210184050","display_name":"Journal on Computing and Cultural Heritage","issn_l":"1556-4673","issn":["1556-4673","1556-4711"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal on Computing and Cultural Heritage","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1962010357","https://openalex.org/W2012210378","https://openalex.org/W2096579040","https://openalex.org/W2111728162","https://openalex.org/W2113808907","https://openalex.org/W2118246710","https://openalex.org/W2412782625","https://openalex.org/W2525579820","https://openalex.org/W2592939477","https://openalex.org/W2604272474","https://openalex.org/W2612690371","https://openalex.org/W2804342109","https://openalex.org/W2901866350","https://openalex.org/W2951133631","https://openalex.org/W2969343193","https://openalex.org/W3011970623","https://openalex.org/W3023742835","https://openalex.org/W3033696290","https://openalex.org/W3047258141","https://openalex.org/W3089215229","https://openalex.org/W3135737375","https://openalex.org/W3161703172","https://openalex.org/W3193940683","https://openalex.org/W3207740732","https://openalex.org/W3209917050","https://openalex.org/W3211858897","https://openalex.org/W4206281756","https://openalex.org/W4210374744","https://openalex.org/W4224308582","https://openalex.org/W4226088306","https://openalex.org/W4247924304","https://openalex.org/W4283525313","https://openalex.org/W4294368584","https://openalex.org/W4306898566","https://openalex.org/W4308327397","https://openalex.org/W4308621049","https://openalex.org/W4311796646","https://openalex.org/W4312853765","https://openalex.org/W4315700771","https://openalex.org/W4316813551","https://openalex.org/W4317103249","https://openalex.org/W4317425485","https://openalex.org/W4319265772","https://openalex.org/W4320018395","https://openalex.org/W4321483963","https://openalex.org/W6640974819"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W2033914206"],"abstract_inverted_index":{"The":[0,108,136,153,178],"rich":[1],"and":[2,17,34,45,57,63,84,147,176,191,240,245],"enduring":[3],"traditional":[4,29,66,98,199,225],"culture":[5],"cultivated":[6],"by":[7,202],"the":[8,15,20,42,61,73,79,85,104,113,117,127,166,189,194,212],"Chinese":[9,21,50],"nation":[10],"over":[11],"millennia":[12],"serves":[13],"as":[14,112,174],"core":[16],"essence":[18],"of":[19,27,48,65,76,81,87,116,139,193],"heritage.":[22],"In":[23],"this":[24,94],"intricate":[25],"tapestry":[26],"culture,":[28],"patterns":[30,38,67],"hold":[31],"a":[32,97,143,148,198,204,224],"significant":[33,69],"revered":[35],"position.":[36],"These":[37],"not":[39],"only":[40],"reflect":[41],"aesthetic":[43],"values":[44],"artistic":[46],"achievements":[47],"ancient":[49],"civilization":[51],"but":[52],"also":[53],"carry":[54],"deep":[55],"cultural":[56],"historical":[58],"significance.":[59],"However,":[60],"segmentation":[62,100,248],"recognition":[64],"pose":[68],"challenges":[70],"due":[71],"to":[72,125,129,161,168,215],"limited":[74,133],"availability":[75],"annotated":[77,134],"data,":[78],"complexity":[80],"pattern":[82,99,200,226,247],"variations,":[83],"interference":[86],"material":[88],"textures.":[89],"To":[90],"address":[91],"these":[92],"challenges,":[93],"article":[95],"proposes":[96],"algorithm":[101,128,137,232],"based":[102],"on":[103,170,217,223],"memory":[105,109],"learning":[106,110],"model.":[107],"model,":[111],"guiding":[114,165],"principle":[115],"algorithm,":[118,209],"leverages":[119],"prior":[120,145,155],"knowledge":[121],"from":[122],"related":[123],"domains":[124],"enable":[126],"generalize":[130],"effectively":[131],"with":[132],"data.":[135],"consists":[138],"two":[140],"key":[141],"components:":[142],"saliency":[144,154,163],"module":[146,156,182],"multi-scale":[149,179],"feature":[150,180],"matching":[151,181],"module.":[152],"uses":[157],"phase":[158,205,218],"spectrum":[159,207],"information":[160,172],"generate":[162],"maps,":[164],"model":[167],"focus":[169,216],"high-frequency":[171],"such":[173],"edges":[175],"contours.":[177],"captures":[183],"features":[184],"at":[185],"different":[186],"scales,":[187],"improving":[188],"robustness":[190,241],"accuracy":[192],"segmentation.":[195],"We":[196],"construct":[197],"dataset":[201,227],"introducing":[203],"spectrum\u2013amplitude":[206],"fusion":[208],"which":[210],"enhances":[211],"model\u2019s":[213],"ability":[214],"consistency":[219],"information.":[220],"Experimental":[221],"results":[222],"show":[228],"that":[229],"our":[230],"proposed":[231],"outperforms":[233],"state-of-the-art":[234],"methods,":[235],"demonstrating":[236],"its":[237],"superior":[238],"performance":[239],"in":[242],"handling":[243],"complex":[244],"diverse":[246],"tasks.":[249]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
