{"id":"https://openalex.org/W2510439625","doi":"https://doi.org/10.1109/prni.2016.7552356","title":"Evaluation of weight sparsity control during autoencoder training of resting-state fMRI using non-zero ratio and hoyer's sparseness","display_name":"Evaluation of weight sparsity control during autoencoder training of resting-state fMRI using non-zero ratio and hoyer's sparseness","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2510439625","doi":"https://doi.org/10.1109/prni.2016.7552356","mag":"2510439625"},"language":"en","primary_location":{"id":"doi:10.1109/prni.2016.7552356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/prni.2016.7552356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI)","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/A5100678501","display_name":"Hyun\u2010Chul Kim","orcid":"https://orcid.org/0000-0001-7943-3295"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyun-chul Kim","raw_affiliation_strings":["Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033376623","display_name":"Jong\u2010Hwan Lee","orcid":"https://orcid.org/0000-0002-8902-6009"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jong-hwan Lee","raw_affiliation_strings":["Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100678501"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":0.4875,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.6583103,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"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/T10241","display_name":"Functional Brain Connectivity Studies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"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":0.7293272018432617},{"id":"https://openalex.org/keywords/human-connectome-project","display_name":"Human Connectome Project","score":0.6135699152946472},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5779978632926941},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5553775429725647},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.551763117313385},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5049570202827454},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4911753833293915},{"id":"https://openalex.org/keywords/resting-state-fmri","display_name":"Resting state fMRI","score":0.4870505630970001},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4763898253440857},{"id":"https://openalex.org/keywords/betweenness-centrality","display_name":"Betweenness centrality","score":0.45895346999168396},{"id":"https://openalex.org/keywords/dependability","display_name":"Dependability","score":0.41081398725509644},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.384278804063797},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38400739431381226},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3136449456214905},{"id":"https://openalex.org/keywords/functional-connectivity","display_name":"Functional connectivity","score":0.24679401516914368},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.169403076171875},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.13902384042739868},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.12148234248161316}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7293272018432617},{"id":"https://openalex.org/C97820695","wikidata":"https://www.wikidata.org/wiki/Q387749","display_name":"Human Connectome Project","level":3,"score":0.6135699152946472},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5779978632926941},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5553775429725647},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.551763117313385},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5049570202827454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4911753833293915},{"id":"https://openalex.org/C66324658","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Resting state fMRI","level":2,"score":0.4870505630970001},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4763898253440857},{"id":"https://openalex.org/C117045392","wikidata":"https://www.wikidata.org/wiki/Q4899215","display_name":"Betweenness centrality","level":3,"score":0.45895346999168396},{"id":"https://openalex.org/C77019957","wikidata":"https://www.wikidata.org/wiki/Q2689057","display_name":"Dependability","level":2,"score":0.41081398725509644},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.384278804063797},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38400739431381226},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3136449456214905},{"id":"https://openalex.org/C3018011982","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Functional connectivity","level":2,"score":0.24679401516914368},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.169403076171875},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.13902384042739868},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.12148234248161316},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","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/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/prni.2016.7552356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/prni.2016.7552356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1457602677","https://openalex.org/W1594793942","https://openalex.org/W2058046532","https://openalex.org/W2090948971","https://openalex.org/W2110798204","https://openalex.org/W2111854888","https://openalex.org/W2115729631","https://openalex.org/W2118718620","https://openalex.org/W2133257461","https://openalex.org/W2157446241","https://openalex.org/W2163922914","https://openalex.org/W2325276834","https://openalex.org/W2562162676","https://openalex.org/W6635741165","https://openalex.org/W6676481782","https://openalex.org/W6677079992","https://openalex.org/W6677759377","https://openalex.org/W6679718588"],"related_works":["https://openalex.org/W2803889471","https://openalex.org/W2953062348","https://openalex.org/W2096672020","https://openalex.org/W2982118753","https://openalex.org/W4280499032","https://openalex.org/W2949154552","https://openalex.org/W3210626554","https://openalex.org/W2945737324","https://openalex.org/W2892680842","https://openalex.org/W3141265783"],"abstract_inverted_index":{"Recently,":[0],"an":[1,107],"explicit":[2],"control":[3,35,88,143,194],"of":[4,31,40,50,54,61,74,83,100,123,136,182,201],"weight":[5,33,113,192],"sparsity":[6,34,56,87,114,142,158,162,193],"level":[7,159],"between":[8],"the":[9,12,29,32,38,51,55,71,81,84,92,98,112,119,124,128,137,141,147,152,165,180,183,191,198],"layers":[10],"in":[11,48],"deep":[13,187],"neural":[14,188],"network":[15,189],"has":[16],"been":[17,21],"proposed":[18],"and":[19,67,102,160,167,176],"gainfully":[20],"utilized":[22],"to":[23,78,110,154,196],"resting-state":[24],"fMRI":[25],"(rfMRI)":[26],"data.":[27],"However,":[28],"reliability":[30,82],"scheme":[36,144,195],"via":[37,145],"percentage":[39],"non-zero":[41],"weights":[42],"(PNZ)":[43],"was":[44,104,132],"not":[45],"systematically":[46,79],"evaluated":[47],"term":[49],"convergence":[52,153],"property":[53],"levels":[57,163],"across":[58],"various":[59],"scenarios":[60],"parameter":[62],"changes":[63],"(i.e.":[64],"learning":[65],"rates":[66],"initial":[68],"weights).":[69],"Thus,":[70],"primary":[72],"aim":[73],"this":[75,117],"study":[76],"is":[77],"evaluate":[80],"PNZ":[85,148,166],"based":[86,96,169],"scheme.":[89],"In":[90],"addition,":[91],"Hoyer's":[93],"sparseness":[94],"(HSP)":[95],"on":[97],"ratio":[99],"L1-":[101],"L2-norms":[103],"adopted":[105],"as":[106,134],"alternative":[108],"option":[109],"measure":[111],"level.":[115],"To":[116],"end,":[118],"whole-brain":[120],"functional":[121],"connectivity":[122],"rfMRI":[125],"data":[126,205],"from":[127,164],"Human":[129],"Connectome":[130],"Project":[131],"used":[133],"input":[135],"autoencoder":[138],"(AE)":[139],"with":[140,190,206],"either":[146],"or":[149],"HSP.":[150],"Then,":[151],"reach":[155],"a":[156],"target":[157],"converged":[161],"HSP":[168],"schemes":[170],"were":[171],"compared.":[172],"The":[173],"presented":[174],"methods":[175],"findings":[177],"will":[178],"benefit":[179],"training":[181],"(stacked-)":[184],"AE":[185],"and/or":[186],"ease":[197],"curse-of-dimensionality":[199],"issue":[200],"very":[202],"highdimensional":[203],"neuroimaging":[204],"limited":[207],"available":[208],"samples.":[209]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}