{"id":"https://openalex.org/W4402915552","doi":"https://doi.org/10.1109/icip51287.2024.10647790","title":"Latent Enhancing Autoencoder for Occluded Image Classification","display_name":"Latent Enhancing Autoencoder for Occluded Image Classification","publication_year":2024,"publication_date":"2024-09-27","ids":{"openalex":"https://openalex.org/W4402915552","doi":"https://doi.org/10.1109/icip51287.2024.10647790"},"language":"en","primary_location":{"id":"doi:10.1109/icip51287.2024.10647790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip51287.2024.10647790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","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/A5076371381","display_name":"Ketan Kotwal","orcid":"https://orcid.org/0000-0003-3766-0881"},"institutions":[{"id":"https://openalex.org/I7495430","display_name":"Idiap Research Institute","ror":"https://ror.org/05932h694","country_code":"CH","type":"facility","lineage":["https://openalex.org/I7495430"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Ketan Kotwal","raw_affiliation_strings":["Idiap Research Institute,Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Idiap Research Institute,Switzerland","institution_ids":["https://openalex.org/I7495430"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043214743","display_name":"Tanay Deshmukh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tanay Deshmukh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5022047576","display_name":"Preeti Gopal","orcid":"https://orcid.org/0000-0002-5470-3911"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Preeti Gopal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"894","last_page":"900"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.7638999819755554,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.7638999819755554,"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/T10862","display_name":"AI in cancer detection","score":0.6973000168800354,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.6241999864578247,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9227057695388794},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6949546337127686},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6367872953414917},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5642126798629761},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5102012157440186},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4930844008922577},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47554370760917664},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2693229913711548}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9227057695388794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6949546337127686},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6367872953414917},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5642126798629761},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5102012157440186},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4930844008922577},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47554370760917664},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2693229913711548}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip51287.2024.10647790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip51287.2024.10647790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4300000071525574}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310531","display_name":"Biomet","ror":"https://ror.org/02bn55144"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1991264156","https://openalex.org/W2194775991","https://openalex.org/W2796249144","https://openalex.org/W3010559878","https://openalex.org/W3011334834","https://openalex.org/W3016664689","https://openalex.org/W3034973071","https://openalex.org/W3097711533","https://openalex.org/W3107828565","https://openalex.org/W3124432240","https://openalex.org/W3144035815","https://openalex.org/W3201743904","https://openalex.org/W4312298950","https://openalex.org/W4385805214","https://openalex.org/W4386083053","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6729484714","https://openalex.org/W6767296273","https://openalex.org/W6845937561","https://openalex.org/W6852029987","https://openalex.org/W6852917902"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2145836866","https://openalex.org/W2291489469","https://openalex.org/W2546503577"],"abstract_inverted_index":{"Large":[0],"occlusions":[1,17,34],"result":[2],"in":[3,7,103],"a":[4,131],"significant":[5],"decline":[6],"image":[8],"classification":[9,23,48,67,78,85,125,149],"accuracy.":[10],"During":[11],"inference,":[12],"diverse":[13],"types":[14],"of":[15,77,88,107],"unseen":[16],"introduce":[18,51],"out-of-distribution":[19],"data":[20],"to":[21,26,82,101,136],"the":[22,66,75,117,120,147,157],"model,":[24],"leading":[25],"accuracy":[27,150,168],"dropping":[28],"as":[29,31],"low":[30],"50%.":[32],"As":[33],"encompass":[35],"spatially":[36],"connected":[37],"regions,":[38],"conventional":[39],"methods":[40],"involving":[41],"feature":[42],"reconstruction":[43,83],"are":[44],"inadequate":[45],"for":[46],"enhancing":[47],"performance.":[49],"We":[50],"LEARN:":[52],"Latent":[53],"Enhancing":[54],"feAture":[55],"Reconstruction":[56],"Network-An":[57],"auto-encoder":[58],"based":[59],"network":[60],"that":[61],"can":[62],"be":[63],"incorporated":[64],"into":[65],"model":[68,164],"before":[69],"its":[70,97,112],"classifier":[71],"head":[72],"without":[73],"modifying":[74],"weights":[76],"model.":[79],"In":[80,141,160],"addition":[81],"and":[84,128,134],"losses,":[86],"training":[87],"LEARN":[89,122],"effectively":[90],"combines":[91],"intra-and":[92],"inter-class":[93],"losses":[94],"calculated":[95],"over":[96,138,156],"latent":[98,105],"space-which":[99],"lead":[100],"improvement":[102],"recovering":[104],"space":[106],"occluded":[108],"data,":[109],"while":[110],"preserving":[111],"class-specific":[113],"discriminative":[114],"information.":[115],"On":[116],"OccludedPASCAL3D+":[118],"dataset,":[119],"proposed":[121],"outperforms":[123],"standard":[124],"models":[126],"(VGG16":[127],"ResNet-50)":[129],"by":[130,151],"large":[132],"margin":[133],"up":[135],"2%":[137,155],"state-of-the-art":[139,158],"methods.":[140,159],"cross-dataset":[142],"testing,":[143],"our":[144,163],"method":[145],"improves":[146],"average":[148],"more":[152],"than":[153],"5":[154],"every":[161],"experiment,":[162],"consistently":[165],"maintains":[166],"excellent":[167],"on":[169],"in-distribution":[170],"data.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
