{"id":"https://openalex.org/W3084720774","doi":"https://doi.org/10.1109/access.2020.3023746","title":"Human Segmentation Based on Compressed Deep Convolutional Neural Network","display_name":"Human Segmentation Based on Compressed Deep Convolutional Neural Network","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3084720774","doi":"https://doi.org/10.1109/access.2020.3023746","mag":"3084720774"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3023746","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3023746","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09195490.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09195490.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100786221","display_name":"Jun Miao","orcid":"https://orcid.org/0000-0002-3258-3322"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210164580","display_name":"National Astronomical Observatories","ror":"https://ror.org/058pyyv44","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210164580"]},{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Miao","raw_affiliation_strings":["Key Laboratory of Lunar and Deep Space Exploration, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China","Key Laboratory of Nondestructive Testing (Ministry of Education), Nanchang Hangkong University, Nanchang, China","School of Aeronautical Manufacturing Engineering, Nanchang Hangkong University, Nanchang, China"],"raw_orcid":"https://orcid.org/0000-0002-3258-3322","affiliations":[{"raw_affiliation_string":"Key Laboratory of Lunar and Deep Space Exploration, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210164580"]},{"raw_affiliation_string":"Key Laboratory of Nondestructive Testing (Ministry of Education), Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]},{"raw_affiliation_string":"School of Aeronautical Manufacturing Engineering, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101572194","display_name":"Keqiang Sun","orcid":"https://orcid.org/0000-0003-0878-7963"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keqiang Sun","raw_affiliation_strings":["School of Aeronautical Manufacturing Engineering, Nanchang Hangkong University, Nanchang, China"],"raw_orcid":"https://orcid.org/0000-0003-0878-7963","affiliations":[{"raw_affiliation_string":"School of Aeronautical Manufacturing Engineering, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101514887","display_name":"Xuan Liao","orcid":"https://orcid.org/0000-0002-7261-3821"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Liao","raw_affiliation_strings":["School of Aeronautical Manufacturing Engineering, Nanchang Hangkong University, Nanchang, China"],"raw_orcid":"https://orcid.org/0000-0002-7261-3821","affiliations":[{"raw_affiliation_string":"School of Aeronautical Manufacturing Engineering, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103010371","display_name":"Lu Leng","orcid":"https://orcid.org/0000-0002-5667-224X"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]},{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN","KR"],"is_corresponding":false,"raw_author_name":"Lu Leng","raw_affiliation_strings":["School of Electrical and Electronic Engineering, College of Engineering, Yonsei University, Seoul, South Korea","School of Software, Nanchang Hangkong University, Nanchang, China"],"raw_orcid":"https://orcid.org/0000-0002-5667-224X","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, College of Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"School of Software, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068628314","display_name":"Jun Chu","orcid":"https://orcid.org/0000-0003-2408-3982"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Chu","raw_affiliation_strings":["School of Software, Nanchang Hangkong University, Nanchang, China"],"raw_orcid":"https://orcid.org/0000-0003-2408-3982","affiliations":[{"raw_affiliation_string":"School of Software, Nanchang Hangkong University, Nanchang, China","institution_ids":["https://openalex.org/I927504317"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.1539,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.7854393,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"8","issue":null,"first_page":"167585","last_page":"167595"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9988999962806702,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9988999962806702,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9957000017166138,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8062088489532471},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7306965589523315},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.6971867084503174},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6853646636009216},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6620773673057556},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5416605472564697},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5378889441490173},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.49496740102767944},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.44904837012290955},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43424785137176514},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.42332765460014343},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.35769087076187134},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3045908808708191},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2021094262599945}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8062088489532471},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7306965589523315},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6971867084503174},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6853646636009216},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6620773673057556},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5416605472564697},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5378889441490173},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.49496740102767944},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.44904837012290955},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43424785137176514},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.42332765460014343},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.35769087076187134},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3045908808708191},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2021094262599945},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3023746","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3023746","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09195490.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:46b103e77e0642f28535b38573c2ff29","is_oa":true,"landing_page_url":"https://doaj.org/article/46b103e77e0642f28535b38573c2ff29","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 167585-167595 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3023746","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3023746","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09195490.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1664196159","display_name":null,"funder_award_id":"CSC201808360294","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G2185407581","display_name":null,"funder_award_id":"ZD201529003","funder_id":"https://openalex.org/F4320311344","funder_display_name":"Nanchang Hangkong University"},{"id":"https://openalex.org/G266751178","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u548c\u8bb0\u5fc6\u673a\u5236\u7684\u590d\u6742\u73af\u5883\u76ee\u6807\u8ddf\u8e2a\u7814\u7a76","funder_award_id":"61663031","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3635034324","display_name":null,"funder_award_id":"LDSE201705","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G4996114763","display_name":null,"funder_award_id":"20171ACE50024","funder_id":"https://openalex.org/F4320326696","funder_display_name":"Jiangxi Provincial Department of Science and Technology"},{"id":"https://openalex.org/G7328915964","display_name":null,"funder_award_id":"CSC201908360075","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G746356759","display_name":null,"funder_award_id":"20192BBE50073","funder_id":"https://openalex.org/F4320326696","funder_display_name":"Jiangxi Provincial Department of Science and Technology"},{"id":"https://openalex.org/G8648020462","display_name":"\u79fb\u52a8\u73af\u5883\u624b\u90e8\u5f02\u8d28\u7279\u5f81\u517c\u5bb9\u6027\u6570\u5b57\u7b7e\u540d\u6280\u672f\u7814\u7a76","funder_award_id":"61866028","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8940430046","display_name":"\u56fe\u50cf\u8bed\u4e49\u4e0e\u4e2d\u3001\u4f4e\u5c42\u7279\u5f81\u67d4\u6027\u878d\u5408\u7684\u57ce\u5e02\u5efa\u7b51\u7269\u4e09\u7ef4\u91cd\u5efa\u7814\u7a76","funder_award_id":"61661036","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320311344","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320326696","display_name":"Jiangxi Provincial Department of Science and Technology","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3084720774.pdf","grobid_xml":"https://content.openalex.org/works/W3084720774.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1724438581","https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W1967268147","https://openalex.org/W2000947714","https://openalex.org/W2037227137","https://openalex.org/W2064741553","https://openalex.org/W2098360446","https://openalex.org/W2112796928","https://openalex.org/W2119144962","https://openalex.org/W2121295188","https://openalex.org/W2124351162","https://openalex.org/W2125637308","https://openalex.org/W2145085734","https://openalex.org/W2161236525","https://openalex.org/W2163605009","https://openalex.org/W2168894214","https://openalex.org/W2194775991","https://openalex.org/W2234281713","https://openalex.org/W2400000673","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2630837129","https://openalex.org/W2736352281","https://openalex.org/W2799197246","https://openalex.org/W2800452261","https://openalex.org/W2896988829","https://openalex.org/W2942672693","https://openalex.org/W2949341804","https://openalex.org/W2952793010","https://openalex.org/W2962851801","https://openalex.org/W2962965870","https://openalex.org/W2963145730","https://openalex.org/W2963163009","https://openalex.org/W2963363373","https://openalex.org/W2964228333","https://openalex.org/W2964233199","https://openalex.org/W2988917872","https://openalex.org/W3006904694","https://openalex.org/W4241807222","https://openalex.org/W6637373629","https://openalex.org/W6637709462","https://openalex.org/W6638667902","https://openalex.org/W6677580257","https://openalex.org/W6684665197","https://openalex.org/W6724670942","https://openalex.org/W6726275242","https://openalex.org/W6734062232","https://openalex.org/W6739696289"],"related_works":["https://openalex.org/W2373300491","https://openalex.org/W4375867731","https://openalex.org/W4391621807","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W2964954556","https://openalex.org/W3103566983","https://openalex.org/W3099765033","https://openalex.org/W2997155179"],"abstract_inverted_index":{"Most":[0],"semantic":[1],"segmentation":[2,41,63,69,196],"models":[3],"based":[4,45],"on":[5,46,60,205],"deep":[6,48],"convolutional":[7],"neural":[8],"network":[9,30,148,157],"(CNN)":[10],"typically":[11],"require":[12],"a":[13,28],"large":[14],"number":[15],"of":[16,89,108,121,128,155],"weight":[17],"parameters,":[18],"high":[19,134],"hardware":[20],"resources":[21],"for":[22],"storage":[23,185],"and":[24,55,79,113,124,160,183,203],"computation.":[25],"Moreover,":[26],"redesigning":[27],"compact":[29],"suffers":[31],"from":[32],"some":[33],"training":[34,150,154],"problems,":[35],"such":[36],"as":[37],"under-fitting.":[38],"A":[39],"human":[40,62,68],"algorithm":[42],"is":[43,58,102,158,162,198],"proposed":[44],"compressed":[47],"CNN":[49],"to":[50,65,166],"optimize":[51],"the":[52,61,67,75,87,90,96,106,122,126,133,147,152,156,167,171,176,195],"convolution":[53],"layers":[54],"filters.":[56],"PSPNet-50":[57],"fine-tuned":[59],"dataset":[64],"obtain":[66],"model":[70,91,123,168],"with":[71,105],"higher":[72],"accuracy.":[73,139],"Then":[74],"convolutional-layer":[76],"level":[77],"pruning":[78,100,112],"corresponding":[80],"structure":[81],"optimization":[82],"are":[83,92,186],"performed":[84],"so":[85],"that":[86,175],"parameters":[88,120],"substantially":[93],"reduced.":[94],"Finally,":[95],"two-stage":[97],"global":[98],"filter-level":[99],"strategy":[101,116],"used.":[103],"Compared":[104,165],"method":[107],"layer":[109,111],"by":[110,142,188,200],"retraining,":[114,129],"our":[115],"not":[117],"only":[118],"reduces":[119],"saves":[125],"time":[127],"but":[130],"also":[131],"keeps":[132],"IoU":[135,161,204],"(Intersection":[136],"over":[137],"Union)":[138],"In":[140],"addition,":[141],"adding":[143],"auxiliary":[144],"losses":[145],"in":[146],"during":[149],"CNN,":[151],"supervised":[153],"improved,":[159],"further":[163],"increased.":[164],"before":[169],"compression,":[170],"sufficient":[172],"experiments":[173],"show":[174],"parameter":[177,184],"number,":[178],"computation":[179],"cost,":[180],"memory":[181],"consumption,":[182],"decreased":[187],"1/7.5,":[189],"5.6/6.6,":[190],"0.7/1,":[191],"6.5/7.5,":[192],"respectively,":[193],"while":[194],"speed":[197],"accelerated":[199],"2.4":[201],"times,":[202],"test":[206],"set":[207],"reaches":[208],"93.2%.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
