{"id":"https://openalex.org/W3000721139","doi":"https://doi.org/10.1145/3369166.3369191","title":"The Effect of Smoothing Filter on CNN based AD Classification","display_name":"The Effect of Smoothing Filter on CNN based AD Classification","publication_year":2019,"publication_date":"2019-10-23","ids":{"openalex":"https://openalex.org/W3000721139","doi":"https://doi.org/10.1145/3369166.3369191","mag":"3000721139"},"language":"en","primary_location":{"id":"doi:10.1145/3369166.3369191","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3369166.3369191","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 8th International Conference on Bioinformatics and Biomedical Science","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/A5090743678","display_name":"Baiwen Zhang","orcid":"https://orcid.org/0000-0003-0035-2391"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Baiwen Zhang","raw_affiliation_strings":["College of Life Science and Bio-engineering, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Life Science and Bio-engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100691578","display_name":"Jingxuan Wang","orcid":"https://orcid.org/0009-0001-1746-9628"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingxuan Wang","raw_affiliation_strings":["College of Life Science and Bio-engineering, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Life Science and Bio-engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081758373","display_name":"Lan Lin","orcid":"https://orcid.org/0000-0002-3431-2753"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lan Lin","raw_affiliation_strings":["College of Life Science and Bio-engineering, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Life Science and Bio-engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063947852","display_name":"Shuicai Wu","orcid":"https://orcid.org/0000-0002-8027-9499"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuicai Wu","raw_affiliation_strings":["College of Life Science and Bio-engineering, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Life Science and Bio-engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5090743678"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.2146,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.60833283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"54","last_page":"58"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9965999722480774,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9959999918937683,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7628390789031982},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.7251946330070496},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7004690170288086},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6776378154754639},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6595606207847595},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6550177931785583},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6003943085670471},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5570347905158997},{"id":"https://openalex.org/keywords/gaussian-blur","display_name":"Gaussian blur","score":0.5549724698066711},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.5374577045440674},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5202952027320862},{"id":"https://openalex.org/keywords/gaussian-filter","display_name":"Gaussian filter","score":0.5193291902542114},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48463279008865356},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4189569056034088},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1836496889591217},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1727730631828308},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15173614025115967},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.12171685695648193},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10334178805351257},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.08575695753097534},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07019612193107605}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7628390789031982},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.7251946330070496},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7004690170288086},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6776378154754639},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6595606207847595},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6550177931785583},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6003943085670471},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5570347905158997},{"id":"https://openalex.org/C104317376","wikidata":"https://www.wikidata.org/wiki/Q1894545","display_name":"Gaussian blur","level":5,"score":0.5549724698066711},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.5374577045440674},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5202952027320862},{"id":"https://openalex.org/C65892221","wikidata":"https://www.wikidata.org/wiki/Q1113935","display_name":"Gaussian filter","level":3,"score":0.5193291902542114},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48463279008865356},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4189569056034088},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1836496889591217},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1727730631828308},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15173614025115967},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.12171685695648193},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10334178805351257},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.08575695753097534},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07019612193107605},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3369166.3369191","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3369166.3369191","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 8th International Conference on Bioinformatics and Biomedical Science","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":19,"referenced_works":["https://openalex.org/W1666219330","https://openalex.org/W1968065637","https://openalex.org/W1973127790","https://openalex.org/W2007044705","https://openalex.org/W2043446004","https://openalex.org/W2057536936","https://openalex.org/W2071128523","https://openalex.org/W2075937340","https://openalex.org/W2119848633","https://openalex.org/W2130371234","https://openalex.org/W2153635508","https://openalex.org/W2155298532","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2399495985","https://openalex.org/W2502949459","https://openalex.org/W2526522512","https://openalex.org/W2888846630","https://openalex.org/W2938768326"],"related_works":["https://openalex.org/W2063769574","https://openalex.org/W2134831563","https://openalex.org/W2083966666","https://openalex.org/W2368921446","https://openalex.org/W4241340242","https://openalex.org/W2391139946","https://openalex.org/W2384692698","https://openalex.org/W2990717236","https://openalex.org/W2549920676","https://openalex.org/W1964389324"],"abstract_inverted_index":{"Gaussian":[0],"smoothing":[1],"(GS)":[2],"is":[3,21,46,79,146,178,183],"a":[4,22,50,82,195],"spatial":[5],"low":[6,180],"pass":[7],"filtering":[8],"method":[9],"widely":[10],"used":[11,119],"in":[12,120],"neuroimaging":[13],"preprocessing.":[14],"Full":[15],"width":[16],"at":[17,175],"half":[18],"maximum":[19],"(FWHM)":[20],"common":[23],"parameter":[24],"when":[25,181],"the":[26,42,56,104,137,148,152,189],"imaging":[27],"data":[28,110,118],"convolved":[29],"with":[30],"GS":[31,62],"kernel.":[32],"The":[33,97,117,172,185],"convolutional":[34],"neural":[35],"networks":[36],"(CNNs)":[37],"can":[38],"be":[39],"considered":[40],"as":[41],"feature":[43,64,88,199],"extractor,":[44],"which":[45,159],"implemented":[47],"by":[48],"applying":[49],"series":[51],"of":[52,58,61,139,169,201],"different":[53],"filters.":[54],"However,":[55],"influence":[57,138],"kernel":[59],"size":[60],"for":[63,87,95,155,164],"extraction":[65,89,200],"remains":[66],"unclear.":[67],"In":[68],"this":[69,121],"study,":[70],"we":[71],"describe":[72],"an":[73],"automatic":[74],"AD":[75,156,204],"classification":[76,142,149,173],"algorithm":[77,98],"that":[78,188],"built":[80],"on":[81,141,198],"pre-trained":[83],"CNN":[84],"model,":[85],"AlexNet":[86,170],"and":[90,101,129,157,167],"support":[91],"vector":[92],"machine":[93],"(SVM)":[94],"classification.":[96,205],"was":[99],"trained":[100],"tested":[102],"using":[103],"structural":[105],"Magnetic":[106],"Resonance":[107],"Imaging":[108],"(sMRI)":[109],"from":[111],"Alzheimer's":[112,125],"Disease":[113],"Neuroimaging":[114],"Initiative":[115],"(ADNI).":[116],"study":[122],"include":[123],"191":[124],"disease":[126],"(AD)":[127],"patients":[128],"103":[130],"normal":[131],"control":[132],"(NC)":[133],"subjects.":[134],"We":[135],"evaluate":[136],"FWHM":[140,145,182],"performance.":[143],"When":[144],"0mm,":[147],"accuracy":[150,174],"obtained":[151],"highest":[153],"value":[154,192],"NC,":[158],"reached":[160],"91.5%,":[161],"92.4%,":[162],"89.0%":[163],"conv3,":[165],"conv4":[166],"conv5":[168],"respectively.":[171],"each":[176],"layer":[177],"relatively":[179],"8mm.":[184],"result":[186],"suggests":[187],"higher":[190],"smooth":[191],"may":[193],"have":[194],"negative":[196],"effect":[197],"CNNs":[202],"during":[203]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}