{"id":"https://openalex.org/W3201783943","doi":"https://doi.org/10.4018/ijaci.2021100101","title":"Deep Self-Organizing Map Neural Networks for Plantar Pressure Image Segmentation Employing Marr-Hildreth Features","display_name":"Deep Self-Organizing Map Neural Networks for Plantar Pressure Image Segmentation Employing Marr-Hildreth Features","publication_year":2021,"publication_date":"2021-09-25","ids":{"openalex":"https://openalex.org/W3201783943","doi":"https://doi.org/10.4018/ijaci.2021100101","mag":"3201783943"},"language":"en","primary_location":{"id":"doi:10.4018/ijaci.2021100101","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijaci.2021100101","pdf_url":null,"source":{"id":"https://openalex.org/S51041755","display_name":"International Journal of Ambient Computing and Intelligence","issn_l":"1941-6237","issn":["1941-6237","1941-6245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Ambient Computing and Intelligence","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/A5110804302","display_name":"Jianlin Han","orcid":null},"institutions":[{"id":"https://openalex.org/I93477617","display_name":"Huizhou University","ror":"https://ror.org/03q3s7962","country_code":"CN","type":"education","lineage":["https://openalex.org/I93477617"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianlin Han","raw_affiliation_strings":["Glorious Sun Guangdong School of Fashion, Huizhou University, Huizhou, China & Huidong Shoes Science and Technology Innovation Center, Huizhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Glorious Sun Guangdong School of Fashion, Huizhou University, Huizhou, China & Huidong Shoes Science and Technology Innovation Center, Huizhou, China","institution_ids":["https://openalex.org/I93477617"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100411862","display_name":"Dan Wang","orcid":"https://orcid.org/0000-0002-9713-2610"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Wang","raw_affiliation_strings":["Tianjin Key Laboratory of Process Measurement and Control, School of Electrical Engineering and Automation, Tianjin University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Process Measurement and Control, School of Electrical Engineering and Automation, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108762896","display_name":"Zairan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]},{"id":"https://openalex.org/I93477617","display_name":"Huizhou University","ror":"https://ror.org/03q3s7962","country_code":"CN","type":"education","lineage":["https://openalex.org/I93477617"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"*Zairan Li","raw_affiliation_strings":["Wenzhou Polytechnic, Wenzhou, China & Tianjin Key Laboratory of Process Measurement and Control, School of Electrical Engineering and Automation, Tianjin University, China & Glorious Sun Guangdong School of Fashion, Huizhou University, Huizhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wenzhou Polytechnic, Wenzhou, China & Tianjin Key Laboratory of Process Measurement and Control, School of Electrical Engineering and Automation, Tianjin University, China & Glorious Sun Guangdong School of Fashion, Huizhou University, Huizhou, China","institution_ids":["https://openalex.org/I162868743","https://openalex.org/I93477617"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035130915","display_name":"Fuqian Shi","orcid":"https://orcid.org/0000-0003-4245-5727"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]},{"id":"https://openalex.org/I4390039325","display_name":"Rutgers Cancer Institute","ror":"https://ror.org/0060x3y55","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I102322142","https://openalex.org/I4390039302","https://openalex.org/I4390039325"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fuqian Shi","raw_affiliation_strings":["Rutgers Cancer Institute of New Jersey, New Brunswick, USA"],"raw_orcid":"https://orcid.org/0000-0003-4245-5727","affiliations":[{"raw_affiliation_string":"Rutgers Cancer Institute of New Jersey, New Brunswick, USA","institution_ids":["https://openalex.org/I102322142","https://openalex.org/I4390039325"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5110804302"],"corresponding_institution_ids":["https://openalex.org/I93477617"],"apc_list":null,"apc_paid":null,"fwci":0.2938,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60423316,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"12","issue":"4","first_page":"1","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11227","display_name":"Diabetic Foot Ulcer Assessment and Management","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11227","display_name":"Diabetic Foot Ulcer Assessment and Management","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13647","display_name":"AI and Big Data Applications","score":0.9218000173568726,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12994","display_name":"Infrared Thermography in Medicine","score":0.9207000136375427,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8025240898132324},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7536929845809937},{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.6567236185073853},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6480007767677307},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5829212069511414},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4627395272254944},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4347767233848572},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4178248941898346},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4110279977321625},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3417195677757263}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8025240898132324},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7536929845809937},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.6567236185073853},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6480007767677307},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5829212069511414},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4627395272254944},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4347767233848572},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4178248941898346},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4110279977321625},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3417195677757263},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/ijaci.2021100101","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijaci.2021100101","pdf_url":null,"source":{"id":"https://openalex.org/S51041755","display_name":"International Journal of Ambient Computing and Intelligence","issn_l":"1941-6237","issn":["1941-6237","1941-6245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Ambient Computing and Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jaci00:v:12:y:2021:i:4:p:1-21","is_oa":false,"landing_page_url":"https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJACI.2021100101","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1729212653","https://openalex.org/W1997545217","https://openalex.org/W2047929955","https://openalex.org/W2065692469","https://openalex.org/W2071755385","https://openalex.org/W2097232416","https://openalex.org/W2548653562","https://openalex.org/W2567942285","https://openalex.org/W2594295319","https://openalex.org/W2750931713","https://openalex.org/W2789527575","https://openalex.org/W2898620395","https://openalex.org/W2899220301","https://openalex.org/W2937581751","https://openalex.org/W2954612366","https://openalex.org/W2963075127","https://openalex.org/W2964028220","https://openalex.org/W2986428765","https://openalex.org/W2991095658","https://openalex.org/W2991165082","https://openalex.org/W3002038669","https://openalex.org/W3007477364","https://openalex.org/W3007488608","https://openalex.org/W3007602269","https://openalex.org/W3017157669","https://openalex.org/W3038566483","https://openalex.org/W3039304403","https://openalex.org/W3085430464","https://openalex.org/W3090835550","https://openalex.org/W3091304782","https://openalex.org/W3093231035","https://openalex.org/W3098525219","https://openalex.org/W3106310598","https://openalex.org/W3112494578","https://openalex.org/W3124773035","https://openalex.org/W3125139346","https://openalex.org/W3127069424","https://openalex.org/W3130566196","https://openalex.org/W3131306119","https://openalex.org/W3143842863"],"related_works":["https://openalex.org/W1647056466","https://openalex.org/W2360214423","https://openalex.org/W2156017042","https://openalex.org/W2137852660","https://openalex.org/W2515715595","https://openalex.org/W2513378678","https://openalex.org/W2543665684","https://openalex.org/W2154143144","https://openalex.org/W1500455187","https://openalex.org/W2049597952"],"abstract_inverted_index":{"Using":[0],"the":[1,9,86,129],"plantar":[2,119],"pressure":[3,120],"imaging":[4,24],"analysis":[5,20],"method":[6,90],"to":[7],"realize":[8],"optimization":[10],"design":[11],"of":[12,23,76,80],"shoe":[13,131],"last":[14],"is":[15,52],"still":[16,26],"relatively":[17],"preliminary.":[18],"The":[19,57,88,117],"and":[21,36,59,69,101,112],"utilization":[22],"data":[25],"have":[27,125],"problems":[28],"such":[29],"as":[30],"single":[31],"processing,":[32],"incomplete":[33],"information":[34],"acquisition,":[35],"poor":[37],"processing":[38],"model":[39],"robustness.":[40],"A":[41],"deep":[42],"self-organizing":[43],"map":[44],"neural":[45,115],"network":[46],"based":[47],"on":[48],"Marr-Hildreth":[49,77],"filter":[50],"(dSOM-wh)":[51],"developed":[53,84],"in":[54,94,128],"this":[55],"research.":[56],"structure":[58],"learning":[60,65],"algorithms":[61],"were":[62],"optimized":[63],"by":[64,105],"vector":[66],"quantization":[67],"(LVQ)":[68],"count":[70],"propagation":[71],"(CP).":[72],"As":[73],"a":[74],"kind":[75],"filter,":[78],"Laplacian":[79],"Gaussian":[81],"(LoG)":[82],"was":[83],"for":[85],"preprocessing.":[87],"proposed":[89],"performed":[91],"high":[92],"effectiveness":[93],"accuracy":[95],"(AC)":[96],"(92.88%),":[97],"sensitive":[98],"(SE)":[99],"(0.8941),":[100],"f-measurement":[102],"(F1)":[103],"(0.8720)":[104],"comparing":[106],"with":[107],"ANN,":[108],"CNN,":[109],"SegNet,":[110],"ResNet,":[111],"pre-trained":[113],"inception-v":[114],"networks.":[116],"classification-based":[118],"biomedical":[121],"functional":[122],"zoning":[123],"technologies":[124],"potential":[126],"applications":[127],"comfort":[130],"production":[132],"industry.":[133]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
