{"id":"https://openalex.org/W4313035002","doi":"https://doi.org/10.1109/access.2022.3213675","title":"Image Recognition and Analysis: A Complex Network-Based Approach","display_name":"Image Recognition and Analysis: A Complex Network-Based Approach","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4313035002","doi":"https://doi.org/10.1109/access.2022.3213675"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3213675","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3213675","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09915598.pdf","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":null,"license_id":null,"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://ieeexplore.ieee.org/ielx7/6287639/6514899/09915598.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035536851","display_name":"Zhuang Ma","orcid":"https://orcid.org/0000-0003-1725-2047"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuang Ma","raw_affiliation_strings":["College of Mathematics and Physics, China University of Geosciences, Beijing, China","College of mathematics and Physics, China University of Geosciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1725-2047","affiliations":[{"raw_affiliation_string":"College of Mathematics and Physics, China University of Geosciences, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]},{"raw_affiliation_string":"College of mathematics and Physics, China University of Geosciences, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091823634","display_name":"Guangdong Huang","orcid":"https://orcid.org/0000-0002-3430-2440"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangdong Huang","raw_affiliation_strings":["College of Mathematics and Physics, China University of Geosciences, Beijing, China","College of mathematics and Physics, China University of Geosciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3430-2440","affiliations":[{"raw_affiliation_string":"College of Mathematics and Physics, China University of Geosciences, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]},{"raw_affiliation_string":"College of mathematics and Physics, China University of Geosciences, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3125743391"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.5249,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71617172,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"10","issue":null,"first_page":"109537","last_page":"109543"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9962000250816345,"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/T10057","display_name":"Face and Expression Recognition","score":0.9925000071525574,"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":0.741567075252533},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6875654458999634},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6498104333877563},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.589568018913269},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5849791169166565},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5191368460655212},{"id":"https://openalex.org/keywords/complex-network","display_name":"Complex network","score":0.5126806497573853},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.48849308490753174},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4615800976753235},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4460667371749878},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.426835298538208},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4253702461719513},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.41453635692596436}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.741567075252533},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6875654458999634},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6498104333877563},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.589568018913269},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5849791169166565},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5191368460655212},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.5126806497573853},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.48849308490753174},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4615800976753235},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4460667371749878},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.426835298538208},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4253702461719513},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.41453635692596436},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3213675","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3213675","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09915598.pdf","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fba431b4e12641b59eef8595e34f91a1","is_oa":true,"landing_page_url":"https://doaj.org/article/fba431b4e12641b59eef8595e34f91a1","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 10, Pp 109537-109543 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3213675","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3213675","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09915598.pdf","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4313035002.pdf","grobid_xml":"https://content.openalex.org/works/W4313035002.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W1678912643","https://openalex.org/W2008104685","https://openalex.org/W2081330983","https://openalex.org/W2097009025","https://openalex.org/W2098693229","https://openalex.org/W2114051435","https://openalex.org/W2124389019","https://openalex.org/W2142883007","https://openalex.org/W2145086237","https://openalex.org/W2167178237","https://openalex.org/W2740363801","https://openalex.org/W2790135169","https://openalex.org/W3046765553","https://openalex.org/W6781385973"],"related_works":["https://openalex.org/W4285411112","https://openalex.org/W2107628111","https://openalex.org/W2085033728","https://openalex.org/W2171299904","https://openalex.org/W2394004323","https://openalex.org/W2398764543","https://openalex.org/W2027335291","https://openalex.org/W4390494008","https://openalex.org/W2922442631","https://openalex.org/W2565656575"],"abstract_inverted_index":{"In":[0,82,129],"existing":[1],"image":[2,10,20,39,63,141],"recognition":[3,33,40,51],"algorithms,":[4],"the":[5,17,23,32,45,78,110,133,136,140,146,151,158,161,165],"position":[6],"and":[7,56,97,116,120,144],"sequence":[8],"of":[9,19,26,47,135,139,160],"pixels":[11],"are":[12],"key":[13],"factors":[14],"that":[15,34,93,109],"affect":[16],"accuracy":[18,52,115],"recognition.":[21],"Therefore,":[22],"topological":[24],"invariance":[25],"complex":[27,36,66,89,95,126],"networks":[28,37,67,79,96],"has":[29,112],"led":[30],"to":[31,38,101,131,156],"applying":[35],"analysis":[41],"will":[42],"significantly":[43],"reduce":[44,157],"impact":[46],"images":[48],"on":[49,62,70,164],"classification":[50,64,91,103,114],"when":[53],"rotation,":[54],"translation,":[55],"scaling":[57],"occur.":[58],"However,":[59],"most":[60],"studies":[61],"by":[65],"have":[68],"focused":[69],"a":[71,87,124],"single":[72,125],"network,":[73],"lacking":[74],"dynamic":[75],"evolution":[76],"with":[77,123],"among":[80],"them.":[81],"this":[83],"paper,":[84],"we":[85],"propose":[86],"new":[88],"network":[90,118,127],"method":[92,111],"combines":[94],"convolutional":[98],"neural":[99],"networks(CNN)":[100],"train":[102],"using":[104],"deep":[105],"learning.":[106],"We":[107],"show":[108],"high":[113],"distinct":[117],"features":[119],"compares":[121],"well":[122],"approach.":[128],"addition,":[130],"make":[132],"distribution":[134],"degree":[137],"histogram":[138],"more":[142],"uniform":[143],"concentrated,":[145],"original":[147],"formula":[148],"for":[149],"calculating":[150],"power":[152,166],"value":[153],"was":[154],"optimized":[155],"influence":[159],"radius":[162],"parameter":[163],"value.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
