{"id":"https://openalex.org/W2897894800","doi":"https://doi.org/10.3390/sym10100479","title":"Local Importance Representation Convolutional Neural Network for Fine-Grained Image Classification","display_name":"Local Importance Representation Convolutional Neural Network for Fine-Grained Image Classification","publication_year":2018,"publication_date":"2018-10-11","ids":{"openalex":"https://openalex.org/W2897894800","doi":"https://doi.org/10.3390/sym10100479","mag":"2897894800"},"language":"en","primary_location":{"id":"doi:10.3390/sym10100479","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym10100479","pdf_url":"https://www.mdpi.com/2073-8994/10/10/479/pdf?version=1539256238","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/10/10/479/pdf?version=1539256238","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012164583","display_name":"Yadong Yang","orcid":"https://orcid.org/0000-0002-5392-4552"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yadong Yang","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333215","display_name":"Xiaofeng Wang","orcid":"https://orcid.org/0000-0001-7592-277X"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofeng Wang","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071179179","display_name":"Hengzheng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengzheng Zhang","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China","institution_ids":["https://openalex.org/I96733725"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012164583"],"corresponding_institution_ids":["https://openalex.org/I96733725"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.425,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.68266295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"10","issue":"10","first_page":"479","last_page":"479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.996999979019165,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9962999820709229,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8118301630020142},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7885542511940002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7254664897918701},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7188714146614075},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.644460916519165},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6213717460632324},{"id":"https://openalex.org/keywords/bilinear-interpolation","display_name":"Bilinear interpolation","score":0.5816085338592529},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5808833837509155},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5737840533256531},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5250232815742493},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5137180089950562},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4604194462299347},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4492435157299042},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32209375500679016},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.31202495098114014}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8118301630020142},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7885542511940002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7254664897918701},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7188714146614075},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.644460916519165},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6213717460632324},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.5816085338592529},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5808833837509155},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5737840533256531},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5250232815742493},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5137180089950562},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4604194462299347},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4492435157299042},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32209375500679016},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.31202495098114014},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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":3,"locations":[{"id":"doi:10.3390/sym10100479","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym10100479","pdf_url":"https://www.mdpi.com/2073-8994/10/10/479/pdf?version=1539256238","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b7c4751a1e584cc1be61670ef565d039","is_oa":true,"landing_page_url":"https://doaj.org/article/b7c4751a1e584cc1be61670ef565d039","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 10, Iss 10, p 479 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/10/10/479/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/sym10100479","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym10100479","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym10100479","pdf_url":"https://www.mdpi.com/2073-8994/10/10/479/pdf?version=1539256238","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"},{"score":0.4699999988079071,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G2030581296","display_name":null,"funder_award_id":"61703267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3330730477","display_name":null,"funder_award_id":"61872231","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7731137914","display_name":null,"funder_award_id":"2017ycx083","funder_id":"https://openalex.org/F4320326300","funder_display_name":"Shanghai Maritime University"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326300","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2897894800.pdf","grobid_xml":"https://content.openalex.org/works/W2897894800.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1496650988","https://openalex.org/W1606858007","https://openalex.org/W1642817248","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1849277567","https://openalex.org/W1928906481","https://openalex.org/W1955942245","https://openalex.org/W2064223554","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2104657103","https://openalex.org/W2109255472","https://openalex.org/W2118696714","https://openalex.org/W2138011018","https://openalex.org/W2163605009","https://openalex.org/W2172099696","https://openalex.org/W2183341477","https://openalex.org/W2196615847","https://openalex.org/W2202499615","https://openalex.org/W2207849498","https://openalex.org/W2339876161","https://openalex.org/W2531409750","https://openalex.org/W2549079750","https://openalex.org/W2549139847","https://openalex.org/W2588744874","https://openalex.org/W2601564443","https://openalex.org/W2681460984","https://openalex.org/W2737725206","https://openalex.org/W2745153189","https://openalex.org/W2752782242","https://openalex.org/W2763070548","https://openalex.org/W2765268259","https://openalex.org/W2773003563","https://openalex.org/W2778955544","https://openalex.org/W2789504340","https://openalex.org/W2791437400","https://openalex.org/W2796672611","https://openalex.org/W2798365843","https://openalex.org/W2807551730","https://openalex.org/W2919115771","https://openalex.org/W2963125010","https://openalex.org/W2963173190","https://openalex.org/W2964350391","https://openalex.org/W6602324145","https://openalex.org/W6618372016","https://openalex.org/W6638319203","https://openalex.org/W6687483927","https://openalex.org/W6703851130","https://openalex.org/W6733711980"],"related_works":["https://openalex.org/W2165589608","https://openalex.org/W2964954556","https://openalex.org/W2911497689","https://openalex.org/W2952813363","https://openalex.org/W2963346891","https://openalex.org/W4360783045","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661"],"abstract_inverted_index":{"Compared":[0],"with":[1,24,102],"ordinary":[2],"image":[3,7,117,164],"classification":[4,8,140,165],"tasks,":[5],"fine-grained":[6,163],"is":[9,17,65,127],"closer":[10],"to":[11,19,78,120],"real-life":[12],"scenes.":[13],"Its":[14],"key":[15],"point":[16],"how":[18],"find":[20],"the":[21,60,68,72,76,87,92,97,103,116,145,156],"local":[22,44,105,113],"areas":[23],"sufficient":[25],"discrimination":[26],"and":[27,84,129,139,151],"perform":[28],"effective":[29],"feature":[30],"learning.":[31],"Based":[32],"on":[33,144],"a":[34,43],"bilinear":[35],"convolutional":[36,47],"neural":[37,48],"network":[38,49,138],"(B-CNN),":[39],"this":[40],"paper":[41],"designs":[42],"importance":[45,106],"representation":[46,107],"(LIR-CNN)":[50],"model,":[51],"which":[52],"can":[53,110],"be":[54],"divided":[55],"into":[56],"three":[57],"parts.":[58],"Firstly,":[59],"super-pixel":[61],"segmentation":[62],"convolution":[63,99,126],"method":[64],"used":[66],"for":[67],"input":[69],"layer":[70],"of":[71,81,91,100,115],"model.":[73],"It":[74,109],"allows":[75],"model":[77,158],"receive":[79],"images":[80],"different":[82],"sizes":[83],"fully":[85],"considers":[86],"complex":[88],"geometric":[89],"deformation":[90],"images.":[93],"Then,":[94],"we":[95],"replaced":[96],"standard":[98],"B-CNN":[101],"proposed":[104,128],"convolution.":[108],"score":[111],"each":[112],"area":[114],"using":[118],"learning":[119],"distinguish":[121],"their":[122],"importance.":[123],"Finally,":[124],"channelwise":[125],"it":[130],"plays":[131],"an":[132],"important":[133],"role":[134],"in":[135,162],"balancing":[136],"lightweight":[137],"accuracy.":[141],"Experimental":[142],"results":[143],"benchmark":[146],"datasets":[147],"(e.g.,":[148],"CUB-200-2011,":[149],"FGVC-Aircraft,":[150],"Stanford":[152],"Cars)":[153],"showed":[154],"that":[155],"LIR-CNN":[157],"had":[159],"good":[160],"performance":[161],"tasks.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}