{"id":"https://openalex.org/W4415708217","doi":"https://doi.org/10.1109/icme59968.2025.11209834","title":"IntegralCAM: Integral-based contribution estimation and visualization for convolutional neural networks","display_name":"IntegralCAM: Integral-based contribution estimation and visualization for convolutional neural networks","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415708217","doi":"https://doi.org/10.1109/icme59968.2025.11209834"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209834","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5028237720","display_name":"Teng\u2010Yok Lee","orcid":"https://orcid.org/0000-0003-1001-381X"},"institutions":[{"id":"https://openalex.org/I4210133125","display_name":"Mitsubishi Electric (Japan)","ror":"https://ror.org/033y26782","country_code":"JP","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Teng-Yok Lee","raw_affiliation_strings":["Mitsubishi Electric Corporation,Information Technology R&D Center,Kamakura,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Corporation,Information Technology R&D Center,Kamakura,Japan","institution_ids":["https://openalex.org/I4210133125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5028237720"],"corresponding_institution_ids":["https://openalex.org/I4210133125"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.7106000185012817,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.7106000185012817,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.07840000092983246,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.04749999940395355,"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":0.6990000009536743},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.5288000106811523},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4884999990463257},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4499000012874603},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44769999384880066},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39649999141693115},{"id":"https://openalex.org/keywords/element","display_name":"Element (criminal law)","score":0.37790000438690186}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6990000009536743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6804999709129333},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5637999773025513},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.5288000106811523},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4884999990463257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4869999885559082},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4499000012874603},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44769999384880066},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39649999141693115},{"id":"https://openalex.org/C200288055","wikidata":"https://www.wikidata.org/wiki/Q2621792","display_name":"Element (criminal law)","level":2,"score":0.37790000438690186},{"id":"https://openalex.org/C158946198","wikidata":"https://www.wikidata.org/wiki/Q131187","display_name":"Taylor series","level":2,"score":0.32260000705718994},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.29490000009536743},{"id":"https://openalex.org/C143587482","wikidata":"https://www.wikidata.org/wiki/Q1543216","display_name":"Iterative and incremental development","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209834","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W2031489346","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2516809705","https://openalex.org/W2616247523","https://openalex.org/W2765793020","https://openalex.org/W2963081790","https://openalex.org/W3010219363","https://openalex.org/W3035253074","https://openalex.org/W4295101687"],"related_works":[],"abstract_inverted_index":{"To":[0],"explain":[1],"how":[2,66],"a":[3,52],"convolutional":[4],"neural":[5],"network":[6],"(CNN)":[7],"processes":[8],"an":[9,72,82],"image,":[10],"it":[11,30],"is":[12,31],"common":[13],"to":[14,20,27,64,77,85,90],"generate":[15,38,123],"classification":[16],"activation":[17],"maps":[18],"(CAMs)":[19],"reveal":[21],"image":[22],"areas":[23],"that":[24,34,120],"are":[25],"relevant":[26],"output.":[28,92],"Nevertheless,":[29],"also":[32],"known":[33],"existing":[35],"methods":[36],"could":[37,122],"unstable":[39],"visualization,":[40],"especially":[41],"for":[42,56,126],"intermediate":[43,73,127],"layers":[44],"inside":[45],"CNNs.":[46],"In":[47],"this":[48],"paper,":[49],"we":[50,101,121],"present":[51],"new":[53],"CAM-generation":[54],"algorithm":[55,84,96,104],"these":[57],"layers.":[58,129],"We":[59],"first":[60],"revisit":[61],"Taylor":[62],"expansion":[63],"estimate":[65],"much":[67],"each":[68],"input":[69],"element":[70],"in":[71],"layer":[74],"locally":[75],"contributes":[76],"the":[78,87,91,99],"function,":[79],"and":[80,115],"derive":[81],"iterative":[83,95],"accumulate":[86],"global":[88],"contribution":[89,113],"Because":[93],"our":[94,103,112],"essentially":[97],"integrates":[98],"contribution,":[100],"call":[102],"Integral-based":[105],"Classification":[106],"Activation":[107],"Maps":[108],"(IntegralCAM).":[109],"By":[110],"combining":[111],"estimation":[114],"element-wise":[116],"weighting,":[117],"experiments":[118],"show":[119],"stable":[124],"CAMs":[125],"CNN":[128]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-30T00:00:00"}