{"id":"https://openalex.org/W4385234458","doi":"https://doi.org/10.1007/978-3-031-37649-8_4","title":"A Novel Process of\u00a0Shoe Pairing Using Computer Vision and\u00a0Deep Learning Methods","display_name":"A Novel Process of\u00a0Shoe Pairing Using Computer Vision and\u00a0Deep Learning Methods","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4385234458","doi":"https://doi.org/10.1007/978-3-031-37649-8_4"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-031-37649-8_4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-37649-8_4","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-031-37649-8_4.pdf","source":{"id":"https://openalex.org/S4210169156","display_name":"Lecture notes in networks and systems","issn_l":"2367-3370","issn":["2367-3370","2367-3389"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Networks and Systems","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/978-3-031-37649-8_4.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063295101","display_name":"Marek Koz\u0142owski","orcid":"https://orcid.org/0000-0002-6313-8387"},"institutions":[{"id":"https://openalex.org/I4210139285","display_name":"National Information Processing Institute","ror":"https://ror.org/040fc1e14","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210139285"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Marek Koz\u0142owski","raw_affiliation_strings":["National Information Processing Institute, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"National Information Processing Institute, Warsaw, Poland","institution_ids":["https://openalex.org/I4210139285"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002752562","display_name":"Przemys\u0142aw Buczkowski","orcid":"https://orcid.org/0000-0002-6374-3456"},"institutions":[{"id":"https://openalex.org/I4210139285","display_name":"National Information Processing Institute","ror":"https://ror.org/040fc1e14","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210139285"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Przemyslaw Buczkowski","raw_affiliation_strings":["National Information Processing Institute, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"National Information Processing Institute, Warsaw, Poland","institution_ids":["https://openalex.org/I4210139285"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027931706","display_name":"Piotr Brzezi\u0144ski","orcid":"https://orcid.org/0000-0001-6817-606X"},"institutions":[{"id":"https://openalex.org/I4210120720","display_name":"\u0141ukasiewicz Research Network - Textile Research Institute","ror":"https://ror.org/01zwfkr30","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210120720"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Piotr Brzezinski","raw_affiliation_strings":["Vive Textile Recycling, Warsaw, Poland"],"affiliations":[{"raw_affiliation_string":"Vive Textile Recycling, Warsaw, Poland","institution_ids":["https://openalex.org/I4210120720"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5063295101"],"corresponding_institution_ids":["https://openalex.org/I4210139285"],"apc_list":null,"apc_paid":null,"fwci":0.4069,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.63120567,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"35","last_page":"44"},"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":0.996399998664856,"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":0.996399998664856,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9936000108718872,"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":0.9929999709129333,"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/pairing","display_name":"Pairing","score":0.8716136813163757},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6713321208953857},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6661757230758667},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6362162828445435},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6316124796867371},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6215419769287109},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5938418507575989},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5446614027023315},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.534910261631012},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5242864489555359},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5210430026054382},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5150756239891052},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48390135169029236},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.45268478989601135},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37800830602645874},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35960835218429565},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.26477551460266113}],"concepts":[{"id":"https://openalex.org/C14103023","wikidata":"https://www.wikidata.org/wiki/Q11681459","display_name":"Pairing","level":3,"score":0.8716136813163757},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6713321208953857},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6661757230758667},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6362162828445435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6316124796867371},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6215419769287109},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5938418507575989},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5446614027023315},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.534910261631012},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5242864489555359},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5210430026054382},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5150756239891052},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48390135169029236},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.45268478989601135},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37800830602645874},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35960835218429565},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26477551460266113},{"id":"https://openalex.org/C54101563","wikidata":"https://www.wikidata.org/wiki/Q124131","display_name":"Superconductivity","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-031-37649-8_4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-37649-8_4","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-031-37649-8_4.pdf","source":{"id":"https://openalex.org/S4210169156","display_name":"Lecture notes in networks and systems","issn_l":"2367-3370","issn":["2367-3370","2367-3389"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Networks and Systems","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-031-37649-8_4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-37649-8_4","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-031-37649-8_4.pdf","source":{"id":"https://openalex.org/S4210169156","display_name":"Lecture notes in networks and systems","issn_l":"2367-3370","issn":["2367-3370","2367-3389"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Networks and Systems","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385234458.pdf"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W358380361","https://openalex.org/W881606563","https://openalex.org/W1481035327","https://openalex.org/W2060534165","https://openalex.org/W2099474155","https://openalex.org/W2114207967","https://openalex.org/W2150590906","https://openalex.org/W2151103935","https://openalex.org/W2161969291","https://openalex.org/W2163352848","https://openalex.org/W2900665190","https://openalex.org/W3148388528","https://openalex.org/W3176694003","https://openalex.org/W4213009331"],"related_works":["https://openalex.org/W4380075502","https://openalex.org/W4295309597","https://openalex.org/W4223943233","https://openalex.org/W4312200629","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W4210794429","https://openalex.org/W3047644063","https://openalex.org/W3140501783","https://openalex.org/W2897745724"],"abstract_inverted_index":{"Abstract":[0],"The":[1,142],"industrialisation":[2],"of":[3,18,25,72,78,89],"the":[4,13,19,132,147],"footwear":[5],"recycling":[6],"processes":[7],"is":[8,97],"a":[9,50,82],"major":[10],"issue":[11],"in":[12,16,28,49,94,105,158],"European":[14],"Union\u2014particularly":[15],"view":[17],"fact":[20],"that":[21,41,102,125],"at":[22],"least":[23],"90%":[24],"shoes":[26],"consumed":[27],"western":[29],"economies":[30],"are":[31,103],"ultimately":[32],"sent":[33],"to":[34,86,112,122],"landfill.":[35],"This":[36,54],"requires":[37],"new":[38],"AI-empowered":[39],"technologies":[40],"enable":[42],"detection,":[43],"classification,":[44],"pairing,":[45,59],"and":[46,75,161],"quality":[47],"assessment":[48],"viable":[51],"automatic":[52,57],"process.":[53],"article":[55,143],"discusses":[56],"shoe":[58,68,93,113],"which":[60],"comprises":[61],"two":[62],"sequential":[63],"stages:":[64],"a)":[65],"deep":[66,128],"multiview":[67,73],"embedding":[69],"(compact":[70],"representation":[71],"data);":[74],"b)":[76],"clustering":[77],"shoes\u2019":[79],"embeddings":[80],"with":[81],"fixed":[83],"similarity":[84],"threshold":[85],"return":[87],"sets":[88],"possible":[90],"pairs.":[91],"Each":[92],"our":[95],"pipeline":[96],"represented":[98],"by":[99,153],"multiple":[100],"images":[101],"collected":[104],"industrial":[106,140],"darkrooms.":[107],"We":[108],"present":[109],"various":[110],"approaches":[111],"pairing\u2014from":[114],"fully":[115],"unsupervised":[116],"ones":[117,124],"based":[118],"on":[119,127],"image":[120],"descriptors":[121],"supervised":[123],"rely":[126],"neural":[129],"networks\u2014to":[130],"identify":[131],"most":[133],"effective":[134],"one":[135],"for":[136],"this":[137],"highly":[138],"specific":[139],"task.":[141],"also":[144],"explains":[145],"how":[146],"selected":[148],"method":[149],"can":[150],"be":[151],"improved":[152],"hyperparameter":[154],"tuning,":[155],"massive":[156],"increases":[157],"training":[159],"data,":[160],"data":[162],"augmentation.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}
