{"id":"https://openalex.org/W2552561459","doi":"https://doi.org/10.1109/ijcnn.2016.7727665","title":"Low level visual feature extraction by learning of multiple tasks for Convolutional Neural Networks","display_name":"Low level visual feature extraction by learning of multiple tasks for Convolutional Neural Networks","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2552561459","doi":"https://doi.org/10.1109/ijcnn.2016.7727665","mag":"2552561459"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727665","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727665","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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/A5112297823","display_name":"Hidenori Ide","orcid":null},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hidenori Ide","raw_affiliation_strings":["Faculty of Engineering, Hiroshima University"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Hiroshima University","institution_ids":["https://openalex.org/I113306721"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086456461","display_name":"Takio Kurita","orcid":"https://orcid.org/0000-0003-3982-6750"},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takio Kurita","raw_affiliation_strings":["Department of Information Engineeiring, Hiroshima University"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineeiring, Hiroshima University","institution_ids":["https://openalex.org/I113306721"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5112297823"],"corresponding_institution_ids":["https://openalex.org/I113306721"],"apc_list":null,"apc_paid":null,"fwci":0.4285,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.79617214,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"3620","last_page":"3627"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994999766349792,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.8446617126464844},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8010267615318298},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.712082028388977},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.7013628482818604},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5860497951507568},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5549684166908264},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5418449640274048},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5196815133094788},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4966886639595032},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48128336668014526},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.46196502447128296},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45534878969192505},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.448800653219223},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.41271230578422546}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8446617126464844},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8010267615318298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.712082028388977},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7013628482818604},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5860497951507568},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5549684166908264},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5418449640274048},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5196815133094788},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4966886639595032},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48128336668014526},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.46196502447128296},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45534878969192505},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.448800653219223},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.41271230578422546},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727665","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727665","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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":30,"referenced_works":["https://openalex.org/W1493910671","https://openalex.org/W1686810756","https://openalex.org/W2073783260","https://openalex.org/W2101926813","https://openalex.org/W2116360511","https://openalex.org/W2117539524","https://openalex.org/W2120480077","https://openalex.org/W2122528955","https://openalex.org/W2122922389","https://openalex.org/W2133013156","https://openalex.org/W2136922672","https://openalex.org/W2145094598","https://openalex.org/W2147800946","https://openalex.org/W2150373663","https://openalex.org/W2163605009","https://openalex.org/W2165644552","https://openalex.org/W2165698076","https://openalex.org/W2169177311","https://openalex.org/W2186489521","https://openalex.org/W2726367589","https://openalex.org/W2913340405","https://openalex.org/W2997574889","https://openalex.org/W4231109964","https://openalex.org/W6637373629","https://openalex.org/W6679564466","https://openalex.org/W6681096077","https://openalex.org/W6684191040","https://openalex.org/W6684671274","https://openalex.org/W6684872329","https://openalex.org/W6687011383"],"related_works":["https://openalex.org/W2821676139","https://openalex.org/W3043695725","https://openalex.org/W4382138864","https://openalex.org/W4387770285","https://openalex.org/W3022215768","https://openalex.org/W3135975972","https://openalex.org/W3016888008","https://openalex.org/W4385864216","https://openalex.org/W4387183713","https://openalex.org/W2165698076"],"abstract_inverted_index":{"Visual":[0],"features":[1],"trained":[2,118,161],"from":[3,37],"large":[4],"scale":[5],"image":[6],"data":[7],"by":[8,72,162],"the":[9,18,25,28,38,42,48,65,69,77,83,86,95,98,109,120,124,127,131,139,143,149,152,156,163],"deep":[10,157],"convolutional":[11,158],"neural":[12,159],"network":[13,160],"can":[14,168],"be":[15,62,117,136],"used":[16],"for":[17,33,64,103,119,138],"other":[19],"visual":[20,173],"tasks.":[21],"This":[22],"paper":[23],"investigates":[24],"effects":[26],"of":[27,30,47,50,76,85,97,100,165],"learning":[29,36,49,99,164],"multiple":[31,51,101,166],"tasks":[32,52,102,167],"such":[34],"transfer":[35],"source":[39],"domains":[40],"to":[41,116],"target":[43,66,121,140],"domain.":[44],"Two":[45],"methods":[46],"are":[53],"considered.":[54],"Also":[55,105],"we":[56,93,106],"investigate":[57],"which":[58],"hidden":[59,78,133],"layers":[60,79,154],"should":[61,135],"re-trained":[63],"task":[67,122,141],"in":[68,142,155],"fine-tuning":[70],"process":[71],"selecting":[73],"a":[74,90],"subset":[75],"and":[80,123,130,151],"updating":[81],"only":[82],"parameters":[84],"selected":[87],"subset.":[88],"Through":[89],"detail":[91],"experiments,":[92],"confirmed":[94],"effectiveness":[96],"pre-training.":[104],"showed":[107],"that":[108,148],"first":[110,150],"layer":[111,134],"is":[112],"not":[113],"always":[114],"required":[115],"fully-connected":[125],"layer,":[126,129],"classifier":[128],"last":[132],"retrained":[137],"fine-tuning.":[144],"These":[145],"results":[146],"suggests":[147],"second":[153],"extract":[169],"general":[170],"low":[171],"level":[172],"features.":[174]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}