{"id":"https://openalex.org/W4404364291","doi":"https://doi.org/10.3389/fnbot.2024.1490198","title":"UnionCAM: enhancing CNN interpretability through denoising, weighted fusion, and selective high-quality class activation mapping","display_name":"UnionCAM: enhancing CNN interpretability through denoising, weighted fusion, and selective high-quality class activation mapping","publication_year":2024,"publication_date":"2024-11-14","ids":{"openalex":"https://openalex.org/W4404364291","doi":"https://doi.org/10.3389/fnbot.2024.1490198","pmid":"https://pubmed.ncbi.nlm.nih.gov/39610839"},"language":"en","primary_location":{"id":"doi:10.3389/fnbot.2024.1490198","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fnbot.2024.1490198","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2024.1490198/pdf","source":{"id":"https://openalex.org/S115606517","display_name":"Frontiers in Neurorobotics","issn_l":"1662-5218","issn":["1662-5218"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Neurorobotics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://public-pages-files-2025.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2024.1490198/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109889457","display_name":"Hao Hu","orcid":"https://orcid.org/0000-0002-9583-2891"},"institutions":[{"id":"https://openalex.org/I4210141966","display_name":"China Academy of Railway Sciences","ror":"https://ror.org/051wv2j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210141966"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Hu","raw_affiliation_strings":["The Center of National Railway Intelligent Transportation System Engineering and Technology, Beijing, China","The Institute of Computing, China Academy of Railway Sciences Corporation Ltd, Beijing, China"],"affiliations":[{"raw_affiliation_string":"The Center of National Railway Intelligent Transportation System Engineering and Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"The Institute of Computing, China Academy of Railway Sciences Corporation Ltd, Beijing, China","institution_ids":["https://openalex.org/I4210141966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107657270","display_name":"Rui Wang","orcid":"https://orcid.org/0009-0001-9714-0637"},"institutions":[{"id":"https://openalex.org/I4210141966","display_name":"China Academy of Railway Sciences","ror":"https://ror.org/051wv2j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210141966"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Wang","raw_affiliation_strings":["The Institute of Computing, China Academy of Railway Sciences Corporation Ltd, Beijing, China"],"affiliations":[{"raw_affiliation_string":"The Institute of Computing, China Academy of Railway Sciences Corporation Ltd, Beijing, China","institution_ids":["https://openalex.org/I4210141966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103181233","display_name":"Hao Lin","orcid":"https://orcid.org/0000-0003-0672-3931"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Lin","raw_affiliation_strings":["Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076179689","display_name":"Huai Yu","orcid":"https://orcid.org/0000-0001-6043-3412"},"institutions":[{"id":"https://openalex.org/I4210141966","display_name":"China Academy of Railway Sciences","ror":"https://ror.org/051wv2j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210141966"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huai Yu","raw_affiliation_strings":["Signal and Communication Research Institute, China Academy of Railway Sciences Corporation Ltd, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Signal and Communication Research Institute, China Academy of Railway Sciences Corporation Ltd, Beijing, China","institution_ids":["https://openalex.org/I4210141966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5109889457"],"corresponding_institution_ids":["https://openalex.org/I4210141966"],"apc_list":{"value":2950,"currency":"USD","value_usd":2950},"apc_paid":{"value":2950,"currency":"USD","value_usd":2950},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18518852,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":null,"first_page":"1490198","last_page":"1490198"},"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":0.9986000061035156,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9965000152587891,"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/interpretability","display_name":"Interpretability","score":0.9183748960494995},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8307477235794067},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7067016363143921},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5132998824119568},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5062231421470642},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4777913987636566},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4516460597515106},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.45124220848083496},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.42643237113952637},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4161713421344757},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1434791386127472}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9183748960494995},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8307477235794067},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7067016363143921},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5132998824119568},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5062231421470642},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4777913987636566},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4516460597515106},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.45124220848083496},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.42643237113952637},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4161713421344757},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1434791386127472}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/fnbot.2024.1490198","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fnbot.2024.1490198","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2024.1490198/pdf","source":{"id":"https://openalex.org/S115606517","display_name":"Frontiers in Neurorobotics","issn_l":"1662-5218","issn":["1662-5218"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Neurorobotics","raw_type":"journal-article"},{"id":"pmid:39610839","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39610839","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in neurorobotics","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11602493","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11602493","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11602493/pdf/fnbot-18-1490198.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Front Neurorobot","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:c2b7b5e7b3ea4249ae58fbb7ee9b920f","is_oa":true,"landing_page_url":"https://doaj.org/article/c2b7b5e7b3ea4249ae58fbb7ee9b920f","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Neurorobotics, Vol 18 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fnbot.2024.1490198","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fnbot.2024.1490198","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2024.1490198/pdf","source":{"id":"https://openalex.org/S115606517","display_name":"Frontiers in Neurorobotics","issn_l":"1662-5218","issn":["1662-5218"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Neurorobotics","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4404364291.pdf","grobid_xml":"https://content.openalex.org/works/W4404364291.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W2037227137","https://openalex.org/W2567959389","https://openalex.org/W2594633041","https://openalex.org/W2765793020","https://openalex.org/W2883554151","https://openalex.org/W2889002172","https://openalex.org/W2949725973","https://openalex.org/W2952020226","https://openalex.org/W2962835968","https://openalex.org/W2963382180","https://openalex.org/W2963715038","https://openalex.org/W2964074081","https://openalex.org/W2965696320","https://openalex.org/W3010219363","https://openalex.org/W3015504877","https://openalex.org/W3037256687","https://openalex.org/W3091921149","https://openalex.org/W3127579051","https://openalex.org/W3138191931","https://openalex.org/W3160358829","https://openalex.org/W3161187512","https://openalex.org/W3173522633","https://openalex.org/W3174863366","https://openalex.org/W3176482836","https://openalex.org/W3215399882","https://openalex.org/W4220822265","https://openalex.org/W4225755289","https://openalex.org/W4236965008","https://openalex.org/W4281764208","https://openalex.org/W4298054042","https://openalex.org/W4300235091","https://openalex.org/W4301409532","https://openalex.org/W4308235908","https://openalex.org/W4311937545","https://openalex.org/W4312736165","https://openalex.org/W4387389931","https://openalex.org/W4392736680","https://openalex.org/W4395056567","https://openalex.org/W4396692080","https://openalex.org/W4401537518","https://openalex.org/W6639204139","https://openalex.org/W6697443983","https://openalex.org/W6751993358","https://openalex.org/W6761231013","https://openalex.org/W6766263406","https://openalex.org/W6768236498","https://openalex.org/W6775305308","https://openalex.org/W6781930375","https://openalex.org/W6794768204","https://openalex.org/W6799352456","https://openalex.org/W6800141065","https://openalex.org/W6849873239","https://openalex.org/W6851983344"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W2133587243","https://openalex.org/W3034789145","https://openalex.org/W4367628250"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1],"neural":[2],"networks":[3],"(CNNs)":[4],"have":[5],"achieved":[6],"remarkable":[7],"success":[8],"in":[9,19,30,76,224,281],"various":[10],"computer":[11],"vision":[12],"tasks.":[13],"However,":[14],"the":[15,38,42,128,141,145,171,178,183,187,230,254,273],"lack":[16],"of":[17,189,245,279],"interpretability":[18],"these":[20,55],"models":[21],"has":[22,45,272],"raised":[23],"concerns":[24],"and":[25,53,123,160,196,215,226,247,259,267],"hindered":[26],"their":[27,74],"widespread":[28],"adoption":[29],"critical":[31],"domains.":[32],"Generating":[33],"activation":[34,62,100,125,172],"maps":[35,63,101],"that":[36,96,114,181],"highlight":[37],"regions":[39],"contributing":[40],"to":[41,51,119,156,166,275],"CNN's":[43],"decision":[44],"emerged":[46],"as":[47,167],"a":[48,104,110,152,239,262],"popular":[49],"approach":[50],"visualize":[52],"interpret":[54],"models.":[56],"Nevertheless,":[57],"existing":[58],"methods":[59],"often":[60],"produce":[61],"contaminated":[64],"with":[65,148],"irrelevant":[66],"background":[67,132,209],"noise":[68,133],"or":[69],"incomplete":[70],"object":[71,213],"activation,":[72],"limiting":[73],"effectiveness":[75],"providing":[77,261],"meaningful":[78],"explanations.":[79,219],"To":[80],"address":[81],"this":[82],"challenge,":[83],"we":[84,164],"propose":[85],"Union":[86],"Class":[87],"Activation":[88],"Mapping":[89],"(UnionCAM),":[90],"an":[91,248],"innovative":[92],"visual":[93,218],"interpretation":[94,185],"framework":[95],"generates":[97],"high-quality":[98],"class":[99],"(CAMs)":[102],"through":[103],"novel":[105,240],"three-step":[106],"approach.":[107],"UnionCAM":[108,220,233,271],"introduces":[109],"weighted":[111,153],"fusion":[112,244],"strategy":[113],"adaptively":[115],"combines":[116],"multiple":[117],"CAMs":[118,135,147,150],"create":[120],"more":[121,158],"informative":[122,161],"comprehensive":[124,159],"maps.":[126],"First,":[127],"denoising":[129,241],"module":[130,143,175],"removes":[131],"from":[134,186],"by":[136,237],"using":[137,151],"adaptive":[138,243],"thresholding.":[139],"Subsequently,":[140],"union":[142],"fuses":[144],"denoised":[146],"region-based":[149],"combination":[154],"scheme":[155],"obtain":[157],"maps,":[162],"which":[163],"refer":[165],"fused":[168,190],"CAMs.":[169,191],"Lastly,":[170],"map":[173],"selection":[174,250],"automatically":[176],"selects":[177],"optimal":[179],"CAM":[180],"offers":[182],"best":[184,231],"pool":[188],"Extensive":[192],"experiments":[193],"on":[194],"ILSVRC2012":[195],"VOC2007":[197],"datasets":[198],"demonstrate":[199],"UnionCAM's":[200],"superior":[201],"performance":[202,258],"over":[203],"state-of-the-art":[204],"methods.":[205],"It":[206,252],"effectively":[207],"suppresses":[208],"noise,":[210],"captures":[211],"complete":[212],"regions,":[214],"provides":[216],"intuitive":[217],"achieves":[221],"significant":[222],"improvements":[223],"insertion":[225],"deletion":[227],"scores,":[228],"outperforming":[229],"baseline.":[232],"makes":[234],"notable":[235],"contributions":[236],"introducing":[238],"strategy,":[242],"CAMs,":[246],"automatic":[249],"mechanism.":[251],"bridges":[253],"gap":[255],"between":[256],"CNN":[257],"interpretability,":[260],"valuable":[263],"tool":[264],"for":[265],"understanding":[266],"trusting":[268],"CNN-based":[269],"systems.":[270],"potential":[274],"foster":[276],"responsible":[277],"deployment":[278],"CNNs":[280],"real-world":[282],"applications.":[283]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}