{"id":"https://openalex.org/W4405513872","doi":"https://doi.org/10.3390/info15120808","title":"WTSM-SiameseNet: A Wood-Texture-Similarity-Matching Method Based on Siamese Networks","display_name":"WTSM-SiameseNet: A Wood-Texture-Similarity-Matching Method Based on Siamese Networks","publication_year":2024,"publication_date":"2024-12-16","ids":{"openalex":"https://openalex.org/W4405513872","doi":"https://doi.org/10.3390/info15120808"},"language":"en","primary_location":{"id":"doi:10.3390/info15120808","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info15120808","pdf_url":"https://www.mdpi.com/2078-2489/15/12/808/pdf?version=1734332137","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/15/12/808/pdf?version=1734332137","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088714179","display_name":"Yizhuo Zhang","orcid":"https://orcid.org/0009-0007-2146-6044"},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yizhuo Zhang","raw_affiliation_strings":["Aliyun School of Big Data, School of Software, School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213161, China"],"affiliations":[{"raw_affiliation_string":"Aliyun School of Big Data, School of Software, School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213161, China","institution_ids":["https://openalex.org/I4210153482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058547744","display_name":"Guanlong Wu","orcid":"https://orcid.org/0000-0002-5462-5167"},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanlei Wu","raw_affiliation_strings":["Aliyun School of Big Data, School of Software, School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213161, China"],"affiliations":[{"raw_affiliation_string":"Aliyun School of Big Data, School of Software, School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213161, China","institution_ids":["https://openalex.org/I4210153482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009076675","display_name":"Shen Shi","orcid":"https://orcid.org/0000-0003-4081-1337"},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shen Shi","raw_affiliation_strings":["Aliyun School of Big Data, School of Software, School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213161, China"],"affiliations":[{"raw_affiliation_string":"Aliyun School of Big Data, School of Software, School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213161, China","institution_ids":["https://openalex.org/I4210153482"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100583081","display_name":"Huiling Yu","orcid":"https://orcid.org/0009-0001-2942-4523"},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiling Yu","raw_affiliation_strings":["Aliyun School of Big Data, School of Software, School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213161, China"],"affiliations":[{"raw_affiliation_string":"Aliyun School of Big Data, School of Software, School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213161, China","institution_ids":["https://openalex.org/I4210153482"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5088714179"],"corresponding_institution_ids":["https://openalex.org/I4210153482"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.2623,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56115486,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"15","issue":"12","first_page":"808","last_page":"808"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13568","display_name":"Wood and Agarwood Research","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13568","display_name":"Wood and Agarwood Research","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"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":0.9606999754905701,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9415000081062317,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/similarity","display_name":"Similarity (geometry)","score":0.6373026371002197},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6202294826507568},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.6109302639961243},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5778066515922546},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5015513896942139},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43679776787757874},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3597763776779175},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2994011640548706},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1730305552482605},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13572227954864502}],"concepts":[{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6373026371002197},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6202294826507568},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.6109302639961243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5778066515922546},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5015513896942139},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43679776787757874},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3597763776779175},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2994011640548706},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1730305552482605},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13572227954864502}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info15120808","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info15120808","pdf_url":"https://www.mdpi.com/2078-2489/15/12/808/pdf?version=1734332137","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d29b37c07f984cb1a9e29eab1d9526f8","is_oa":true,"landing_page_url":"https://doaj.org/article/d29b37c07f984cb1a9e29eab1d9526f8","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 15, Iss 12, p 808 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info15120808","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info15120808","pdf_url":"https://www.mdpi.com/2078-2489/15/12/808/pdf?version=1734332137","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405513872.pdf","grobid_xml":"https://content.openalex.org/works/W4405513872.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W2760923572","https://openalex.org/W2773198688","https://openalex.org/W2811483141","https://openalex.org/W2886145195","https://openalex.org/W2978092824","https://openalex.org/W2999452437","https://openalex.org/W3010256375","https://openalex.org/W3014182430","https://openalex.org/W3017136408","https://openalex.org/W3033114334","https://openalex.org/W3036052796","https://openalex.org/W3046002912","https://openalex.org/W3098636586","https://openalex.org/W3112734495","https://openalex.org/W3128719870","https://openalex.org/W3129458182","https://openalex.org/W3156011792","https://openalex.org/W3160694286","https://openalex.org/W3164581645","https://openalex.org/W3165529460","https://openalex.org/W3193389705","https://openalex.org/W4211207215","https://openalex.org/W4283746543","https://openalex.org/W4367307944","https://openalex.org/W4377229921","https://openalex.org/W4380365840","https://openalex.org/W4386076385","https://openalex.org/W4386253477","https://openalex.org/W4390871942","https://openalex.org/W4394007483","https://openalex.org/W6776530645","https://openalex.org/W6852651891"],"related_works":["https://openalex.org/W1972035260","https://openalex.org/W2375480909","https://openalex.org/W2353314428","https://openalex.org/W2012019886","https://openalex.org/W4301594054","https://openalex.org/W2166090428","https://openalex.org/W2794488505","https://openalex.org/W2381021552","https://openalex.org/W2354749003","https://openalex.org/W2377121353"],"abstract_inverted_index":{"In":[0],"tasks":[1],"such":[2],"as":[3],"wood":[4,91,217],"defect":[5],"repair":[6],"and":[7,36,87,148,178,184,246,264],"the":[8,15,18,30,42,51,75,80,97,129,137,167,176,181,185,193,237,254],"production":[9],"of":[10,17,61,139,170,180,195,199,222,234],"high-end":[11],"wooden":[12],"furniture,":[13],"ensuring":[14],"consistency":[16],"texture":[19,171,218],"in":[20,45,101,244,250],"repaired":[21],"or":[22],"jointed":[23],"areas":[24],"is":[25,202],"crucial.":[26],"This":[27,73,162],"paper":[28],"proposes":[29,153],"WTSM-SiameseNet":[31,230],"model":[32,76,200,210],"for":[33],"wood-texture-similarity":[34],"matching":[35],"introduces":[37],"several":[38],"improvements":[39],"to":[40,49,59,77,131,135,253,258],"address":[41,50,109],"issues":[43,138],"present":[44],"traditional":[46,102],"methods.":[47],"First,":[48],"issue":[52,194],"that":[53,127,144,229],"fixed":[54],"receptive":[55,82],"fields":[56],"cannot":[57],"adapt":[58],"textures":[60,92],"different":[62,94],"sizes,":[63],"a":[64,111,123,154,196,216,241,247],"multi-receptive":[65],"field":[66],"fusion":[67,142,156],"feature":[68,141,155,160],"extraction":[69],"network":[70],"was":[71,115],"designed.":[72],"allows":[74],"autonomously":[78],"select":[79],"optimal":[81],"field,":[83],"enhancing":[84],"its":[85],"flexibility":[86],"accuracy":[88,233,245,260],"when":[89],"handling":[90],"at":[93],"scales.":[95],"Secondly,":[96],"interdependencies":[98],"between":[99],"layers":[100],"serial":[103],"attention":[104,113],"mechanisms":[105],"limit":[106],"performance.":[107,211],"To":[108],"this,":[110],"concurrent":[112],"mechanism":[114],"designed,":[116],"which":[117],"reduces":[118],"interlayer":[119],"interference":[120],"by":[121,188,262,267],"using":[122,215],"dual-stream":[124],"parallel":[125],"structure":[126,147,169],"enhances":[128],"ability":[130],"capture":[132],"features.":[133],"Furthermore,":[134],"overcome":[136],"existing":[140],"methods":[143],"disrupt":[145],"spatial":[146,168],"lack":[149],"interpretability,":[150],"this":[151],"study":[152],"method":[157],"based":[158],"on":[159,236],"correlation.":[161],"approach":[163],"not":[164],"only":[165],"preserves":[166],"features":[172,183],"but":[173],"also":[174],"improves":[175],"interpretability":[177],"stability":[179],"fused":[182],"model.":[186],"Finally,":[187],"introducing":[189],"depthwise":[190],"separable":[191],"convolutions,":[192],"large":[197],"number":[198],"parameters":[201],"addressed,":[203],"significantly":[204],"improving":[205],"training":[206],"efficiency":[207],"while":[208],"maintaining":[209],"Experiments":[212],"were":[213],"conducted":[214],"similarity":[219],"dataset":[220],"consisting":[221],"7588":[223],"image":[224],"pairs.":[225],"The":[226],"results":[227],"show":[228],"achieved":[231],"an":[232],"96.67%":[235],"test":[238],"set,":[239],"representing":[240],"12.91%":[242],"improvement":[243,249],"14.21%":[248],"precision":[251,265],"compared":[252],"pre-improved":[255],"SiameseNet.":[256],"Compared":[257],"CS-SiameseNet,":[259],"increased":[261],"2.86%,":[263],"improved":[266],"6.58%.":[268]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-12T06:13:28.667946","created_date":"2025-10-10T00:00:00"}