{"id":"https://openalex.org/W4312702725","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892108","title":"CAMRI Loss: Improving Recall of a Specific Class without Sacrificing Accuracy","display_name":"CAMRI Loss: Improving Recall of a Specific Class without Sacrificing Accuracy","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312702725","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892108"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892108","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5084378373","display_name":"Daiki Nishiyama","orcid":null},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]},{"id":"https://openalex.org/I24254649","display_name":"Tsukuba University of Technology","ror":"https://ror.org/057bx9y85","country_code":"JP","type":"education","lineage":["https://openalex.org/I24254649"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Daiki Nishiyama","raw_affiliation_strings":["University of Tsukuba / RIKEN AIP,Tsukuba,Ibaraki,Japan","University of Tsukuba / RIKEN AIP, Tsukuba, Ibaraki, Japan"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba / RIKEN AIP,Tsukuba,Ibaraki,Japan","institution_ids":["https://openalex.org/I146399215","https://openalex.org/I24254649"]},{"raw_affiliation_string":"University of Tsukuba / RIKEN AIP, Tsukuba, Ibaraki, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008914720","display_name":"Kazuto Fukuchi","orcid":"https://orcid.org/0000-0003-3895-219X"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]},{"id":"https://openalex.org/I24254649","display_name":"Tsukuba University of Technology","ror":"https://ror.org/057bx9y85","country_code":"JP","type":"education","lineage":["https://openalex.org/I24254649"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuto Fukuchi","raw_affiliation_strings":["University of Tsukuba / RIKEN AIP,Tsukuba,Ibaraki,Japan","University of Tsukuba / RIKEN AIP, Tsukuba, Ibaraki, Japan"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba / RIKEN AIP,Tsukuba,Ibaraki,Japan","institution_ids":["https://openalex.org/I146399215","https://openalex.org/I24254649"]},{"raw_affiliation_string":"University of Tsukuba / RIKEN AIP, Tsukuba, Ibaraki, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038757231","display_name":"Youhei Akimoto","orcid":"https://orcid.org/0000-0003-2760-8123"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]},{"id":"https://openalex.org/I24254649","display_name":"Tsukuba University of Technology","ror":"https://ror.org/057bx9y85","country_code":"JP","type":"education","lineage":["https://openalex.org/I24254649"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Youhei Akimoto","raw_affiliation_strings":["University of Tsukuba / RIKEN AIP,Tsukuba,Ibaraki,Japan","University of Tsukuba / RIKEN AIP, Tsukuba, Ibaraki, Japan"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba / RIKEN AIP,Tsukuba,Ibaraki,Japan","institution_ids":["https://openalex.org/I146399215","https://openalex.org/I24254649"]},{"raw_affiliation_string":"University of Tsukuba / RIKEN AIP, Tsukuba, Ibaraki, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022139141","display_name":"Jun Sakuma","orcid":"https://orcid.org/0000-0001-5015-3812"},"institutions":[{"id":"https://openalex.org/I24254649","display_name":"Tsukuba University of Technology","ror":"https://ror.org/057bx9y85","country_code":"JP","type":"education","lineage":["https://openalex.org/I24254649"]},{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jun Sakuma","raw_affiliation_strings":["University of Tsukuba / RIKEN AIP,Tsukuba,Ibaraki,Japan","University of Tsukuba / RIKEN AIP, Tsukuba, Ibaraki, Japan"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba / RIKEN AIP,Tsukuba,Ibaraki,Japan","institution_ids":["https://openalex.org/I146399215","https://openalex.org/I24254649"]},{"raw_affiliation_string":"University of Tsukuba / RIKEN AIP, Tsukuba, Ibaraki, Japan","institution_ids":["https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5084378373"],"corresponding_institution_ids":["https://openalex.org/I146399215","https://openalex.org/I24254649"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15723982,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"98","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998000264167786,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9980999827384949,"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/margin","display_name":"Margin (machine learning)","score":0.7167683839797974},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.6783687472343445},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6160309314727783},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6111159324645996},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.47631701827049255},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4747229814529419},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4725865125656128},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4481830894947052},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3852061629295349},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38110101222991943},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3295360803604126},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.21918338537216187}],"concepts":[{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7167683839797974},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.6783687472343445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6160309314727783},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6111159324645996},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.47631701827049255},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4747229814529419},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4725865125656128},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4481830894947052},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3852061629295349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38110101222991943},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3295360803604126},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21918338537216187},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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:10.1109/ijcnn55064.2022.9892108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892108","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1902954959","display_name":null,"funder_award_id":"JPMJCR21D3","funder_id":"https://openalex.org/F4320334789","funder_display_name":"Japan Science and Technology Agency"},{"id":"https://openalex.org/G4826549480","display_name":null,"funder_award_id":"JPMJCR21D3","funder_id":"https://openalex.org/F4320338075","funder_display_name":"Core Research for Evolutional Science and Technology"},{"id":"https://openalex.org/G7280246059","display_name":null,"funder_award_id":"19H04164,18H04099","funder_id":"https://openalex.org/F4320320212","funder_display_name":"Japan Society for the Promotion of Science London"}],"funders":[{"id":"https://openalex.org/F4320320212","display_name":"Japan Society for the Promotion of Science London","ror":"https://ror.org/02m7axw05"},{"id":"https://openalex.org/F4320334789","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19"},{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W167016754","https://openalex.org/W562660536","https://openalex.org/W1522301498","https://openalex.org/W1607965943","https://openalex.org/W2112796928","https://openalex.org/W2117876524","https://openalex.org/W2139393465","https://openalex.org/W2145607950","https://openalex.org/W2158131535","https://openalex.org/W2271840356","https://openalex.org/W2507319753","https://openalex.org/W2766557427","https://openalex.org/W2784163702","https://openalex.org/W2910187721","https://openalex.org/W2962898354","https://openalex.org/W2963466847","https://openalex.org/W2963499153","https://openalex.org/W2963656735","https://openalex.org/W2969985801","https://openalex.org/W2997604048","https://openalex.org/W3022509031","https://openalex.org/W3103152812","https://openalex.org/W3118608800","https://openalex.org/W4293478066","https://openalex.org/W6606837198","https://openalex.org/W6615672858","https://openalex.org/W6680919041","https://openalex.org/W6682962330","https://openalex.org/W6735013348"],"related_works":["https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2952760143","https://openalex.org/W2017776670","https://openalex.org/W2347897961","https://openalex.org/W2340870721","https://openalex.org/W2358318464","https://openalex.org/W2979236518","https://openalex.org/W2994927414"],"abstract_inverted_index":{"In":[0,27,199],"real-world":[1],"applications":[2],"of":[3,40,49,66,112,137,166,172,213],"multi-class":[4],"classification":[5],"models,":[6],"misclassification":[7],"in":[8,21,188],"an":[9,41],"important":[10,42,68,139,148,174,186,207],"class":[11,43,69,140,175,187],"(e.g.,":[12,24],"stop":[13],"sign)":[14],"can":[15,36,122,133],"be":[16],"significantly":[17],"more":[18],"harmful":[19],"than":[20,71],"other":[22,73,93,178,215],"classes":[23,179,208],"speed":[25],"limit).":[26],"this":[28],"paper,":[29],"we":[30,60,127],"propose":[31,128],"a":[32,80,99,129,194],"loss":[33,85,130,159,237],"function":[34,131],"that":[35,78,97,132,224],"improve":[37,88,123,134,229],"the":[38,46,52,64,67,72,89,92,95,102,105,109,113,124,135,138,143,147,164,173,182,185,189,197,202,206,211,214,225],"recall":[39,233],"while":[44],"maintaining":[45],"same":[47],"level":[48],"accuracy":[50],"as":[51],"case":[53],"using":[54],"cross-entropy":[55,84,236],"loss.":[56],"For":[57],"our":[58],"purpose,":[59],"need":[61],"to":[62,101,119,162,177,181,196,231],"make":[63],"separation":[65,136,212],"better":[70],"classes.":[74,216],"However,":[75],"existing":[76],"methods":[77],"give":[79],"class-sensitive":[81],"penalty":[82,195,203],"for":[83,146],"do":[86],"not":[87],"separation.":[90,125],"On":[91],"hand,":[94],"method":[96,227],"gives":[98],"margin":[100,144,183],"angle":[103],"between":[104,168],"feature":[106,121,190],"vectors":[107,111],"and":[108,170,221],"weight":[110],"last":[114],"fully":[115],"connected":[116],"layer":[117],"corresponding":[118],"each":[120],"Therefore,":[126],"by":[141,192],"setting":[142],"only":[145,204],"class,":[149],"called":[150],"Class-sensitive":[151],"Additive":[152],"Angular":[153],"Margin":[154],"Loss":[155],"(CAMRI":[156],"Loss).":[157],"CAMRI":[158],"is":[160],"expected":[161],"reduce":[163],"variance":[165],"angles":[167],"features":[169],"weights":[171],"relative":[176],"due":[180],"around":[184],"space":[191],"adding":[193],"angle.":[198],"addition,":[200],"concentrating":[201],"on":[205,218,235],"hardly":[209],"sacrifices":[210],"Experiments":[217],"CIFAR-10,":[219],"GTSRB,":[220],"AwA2":[222],"showed":[223],"proposed":[226],"could":[228],"up":[230],"9%":[232],"improvement":[234],"without":[238],"sacrificing":[239],"accuracy.":[240]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}