{"id":"https://openalex.org/W3048862992","doi":"https://doi.org/10.1109/jstsp.2020.3006323","title":"Editorial: Special Issue on Compact Deep Neural Networks With Industrial Applications","display_name":"Editorial: Special Issue on Compact Deep Neural Networks With Industrial Applications","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3048862992","doi":"https://doi.org/10.1109/jstsp.2020.3006323","mag":"3048862992"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2020.3006323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2020.3006323","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},"type":"editorial","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09145577,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"4","first_page":"605","last_page":"608"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.8605999946594238,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.8605999946594238,"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/T12676","display_name":"Machine Learning and ELM","score":0.7986000180244446,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.7458000183105469,"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":0.6231849789619446},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.540388822555542},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44421109557151794},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43450745940208435}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6231849789619446},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.540388822555542},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44421109557151794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43450745940208435}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstsp.2020.3006323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2020.3006323","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.550000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W2939353110","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756"],"abstract_inverted_index":{"The":[0],"twenty-five":[1],"papers":[2],"in":[3,29,62,117,141,205],"this":[4],"special":[5],"issue":[6,186],"focus":[7],"on":[8,46,189],"industrial":[9],"applications":[10,96],"that":[11,172,196],"deplpoy":[12],"compact":[13,127,165,178],"deep":[14],"neural":[15,18,55,58,82,130,158],"networks.":[16],"Artificial":[17],"netorks":[19],"have":[20,115],"been":[21],"adopted":[22],"for":[23,153,177,182,200],"a":[24,74,101,108],"broad":[25],"range":[26],"of":[27,49,68,80,89,100,111,119,129,133,138],"tasks":[28],"areas":[30],"like":[31],"multimedia":[32],"analysis":[33],"and":[34,53,65,84,122,167,193,203],"processing,":[35],"media":[36],"coding,":[37],"data":[38,71],"analytics,":[39],"etc.":[40],"Their":[41],"recent":[42],"success":[43],"is":[44],"based":[45],"the":[47,63,66,76,85,98,142,206],"feasibility":[48],"processing":[50,120],"much":[51],"larger":[52,109],"complex":[54],"networks":[56,83,131,159],"(deep":[57],"networks,":[59],"DNNs)":[60],"than":[61],"past,":[64],"availability":[67],"large-scale":[69],"training":[70],"sets.":[72],"As":[73],"consequence,":[75],"large":[77],"memory":[78],"footprint":[79],"trained":[81,103],"high":[86],"computational":[87],"complexity":[88],"performing":[90],"inference":[91],"cannot":[92],"be":[93,150,198],"neglected.":[94],"Many":[95],"require":[97],"deployment":[99],"particularly":[102],"network":[104],"instance,":[105],"potentially":[106],"to":[107,149,156,169],"number":[110],"devices,":[112],"which":[113],"may":[114,197],"limitations":[116],"terms":[118],"power":[121],"memory.":[123],"For":[124],"such":[125],"applications,":[126],"representations":[128,171],"are":[132,145],"increasing":[134],"relevance.":[135],"In":[136],"spite":[137],"active":[139],"research":[140],"area,":[143],"there":[144],"still":[146],"open":[147],"questions":[148,192],"clarified":[151],"concerning,":[152],"example,":[154],"how":[155,168],"train":[157],"with":[160],"optimal":[161],"performance":[162],"while":[163],"achieving":[164],"representations,":[166],"achieve":[170],"do":[173],"not":[174],"only":[175],"allow":[176],"transmission,":[179],"but":[180],"also":[181],"efficient":[183],"inference.":[184],"This":[185],"sheds":[187],"light":[188],"these":[190],"important":[191],"provides":[194],"answers":[195],"useful":[199],"both":[201],"practitioners":[202],"researchers":[204],"field.":[207]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}