{"id":"https://openalex.org/W3003224044","doi":"https://doi.org/10.1109/icumt48472.2019.8970918","title":"Upsampling Algorithms for Autoencoder Segmentation Neural Networks: A Comparison Study","display_name":"Upsampling Algorithms for Autoencoder Segmentation Neural Networks: A Comparison Study","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W3003224044","doi":"https://doi.org/10.1109/icumt48472.2019.8970918","mag":"3003224044"},"language":"en","primary_location":{"id":"doi:10.1109/icumt48472.2019.8970918","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icumt48472.2019.8970918","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)","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/A5036154051","display_name":"Martin Kola\u0159\u00edk","orcid":"https://orcid.org/0000-0001-6158-6162"},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":true,"raw_author_name":"Martin Kolarik","raw_affiliation_strings":["Brno University of Technology,Dept. of Telecommunications and SIX Research Center,Brno,Czech Republic","Dept. of Telecommunications and SIX Research Center, Brno University of Technology, Brno, Czech Republic"],"affiliations":[{"raw_affiliation_string":"Brno University of Technology,Dept. of Telecommunications and SIX Research Center,Brno,Czech Republic","institution_ids":["https://openalex.org/I60587646"]},{"raw_affiliation_string":"Dept. of Telecommunications and SIX Research Center, Brno University of Technology, Brno, Czech Republic","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036042625","display_name":"Radim B\u00fcrget","orcid":"https://orcid.org/0000-0003-1849-5390"},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Radim Burget","raw_affiliation_strings":["Brno University of Technology,Dept. of Telecommunications and SIX Research Center,Brno,Czech Republic","Dept. of Telecommunications and SIX Research Center, Brno University of Technology, Brno, Czech Republic"],"affiliations":[{"raw_affiliation_string":"Brno University of Technology,Dept. of Telecommunications and SIX Research Center,Brno,Czech Republic","institution_ids":["https://openalex.org/I60587646"]},{"raw_affiliation_string":"Dept. of Telecommunications and SIX Research Center, Brno University of Technology, Brno, Czech Republic","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061350050","display_name":"Kamil \u0158\u00edha","orcid":"https://orcid.org/0000-0002-6196-5215"},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Kamil Riha","raw_affiliation_strings":["Brno University of Technology,Dept. of Telecommunications and SIX Research Center,Brno,Czech Republic","Dept. of Telecommunications and SIX Research Center, Brno University of Technology, Brno, Czech Republic"],"affiliations":[{"raw_affiliation_string":"Brno University of Technology,Dept. of Telecommunications and SIX Research Center,Brno,Czech Republic","institution_ids":["https://openalex.org/I60587646"]},{"raw_affiliation_string":"Dept. of Telecommunications and SIX Research Center, Brno University of Technology, Brno, Czech Republic","institution_ids":["https://openalex.org/I60587646"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036154051"],"corresponding_institution_ids":["https://openalex.org/I60587646"],"apc_list":null,"apc_paid":null,"fwci":0.2934,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.56735664,"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":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9954000115394592,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9916999936103821,"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/upsampling","display_name":"Upsampling","score":0.9760562181472778},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7006874084472656},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6799007654190063},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6394999623298645},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6075235605239868},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4613649249076843},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.4593806862831116},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45539090037345886},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43591606616973877},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.41981613636016846},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37946462631225586},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.3404473066329956},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21868664026260376}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.9760562181472778},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7006874084472656},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6799007654190063},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6394999623298645},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6075235605239868},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4613649249076843},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.4593806862831116},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45539090037345886},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43591606616973877},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41981613636016846},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37946462631225586},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.3404473066329956},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21868664026260376}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icumt48472.2019.8970918","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icumt48472.2019.8970918","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)","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":16,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1523493493","https://openalex.org/W1745334888","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1909740415","https://openalex.org/W1993947467","https://openalex.org/W2119878957","https://openalex.org/W2559597482","https://openalex.org/W2609077090","https://openalex.org/W2903226808","https://openalex.org/W2964121744","https://openalex.org/W2964151039","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6757040593"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2752972570","https://openalex.org/W4297051394","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W2607795551"],"abstract_inverted_index":{"This":[0,53],"paper":[1,54],"compares":[2],"nine":[3],"different":[4,71,91,145],"upsampling":[5,40,58,89,111,125,146],"methods":[6],"used":[7,150],"in":[8,12,33,41,60,139,151],"convolutional":[9,93],"neural":[10,26,68],"networks":[11,27,143],"terms":[13],"of":[14,21,29,38,45,64,129,155],"accuracy":[15,128],"and":[16,36,76,82,131,137],"processing":[17],"speed.":[18],"The":[19,95,119,148],"process":[20,59],"image":[22,31,39,51,88],"segmentation":[23,160],"using":[24,90,106,121,144],"autoencoder":[25],"consists":[28],"the":[30,34,42,46,57,61,65,100,115],"downsampling":[32],"encoder":[35],"correspondingly":[37],"decoder":[43,62],"part":[44,63],"network":[47,120],"to":[48],"achieve":[49],"original":[50],"resolution.":[52],"focuses":[55],"on":[56],"standard":[66],"U-Net":[67],"network.":[69],"Three":[70],"interpolations":[72],"are":[73],"compared":[74],"with":[75,141],"without":[77],"subsequent":[78],"lxl":[79],"convolution":[80,85],"layers":[81,86],"three":[83],"transpose":[84],"for":[87],"size":[92],"cores.":[94],"experiment":[96],"has":[97,132],"shown":[98,133],"that":[99],"best":[101],"practical":[102],"results":[103],"were":[104],"achieved":[105,126],"simple":[107],"nearest":[108,122],"neighbor":[109,123],"interpolation":[110,124],"taking":[112],"into":[113],"consideration":[114],"computational":[116],"time":[117,136],"needed.":[118],"pixel":[127],"99.47%":[130],"fast":[134],"training":[135],"convergence":[138],"comparison":[140],"other":[142],"methods.":[147],"data":[149],"this":[152],"work":[153],"consist":[154],"a":[156],"lumbar":[157],"CT":[158],"spine":[159],"dataset.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
