{"id":"https://openalex.org/W2755734653","doi":"https://doi.org/10.1109/icip.2017.8296808","title":"Fast and accurate image recognition using Deeply-Fused Branchy Networks","display_name":"Fast and accurate image recognition using Deeply-Fused Branchy Networks","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2755734653","doi":"https://doi.org/10.1109/icip.2017.8296808","mag":"2755734653"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5102290387","display_name":"Mou-Yue Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Mou-Yue Huang","raw_affiliation_strings":["Institute of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101468503","display_name":"Ching-Hao Lai","orcid":"https://orcid.org/0000-0001-9488-1598"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ching-Hao Lai","raw_affiliation_strings":["Institute of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015529786","display_name":"Sin\u2010Horng Chen","orcid":"https://orcid.org/0000-0002-9820-2318"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Sin-Horng Chen","raw_affiliation_strings":["Institute of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102290387"],"corresponding_institution_ids":["https://openalex.org/I148366613"],"apc_list":null,"apc_paid":null,"fwci":0.2731,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.64082667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"2","issue":null,"first_page":"2876","last_page":"2880"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991999864578247,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.9112458229064941},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7424893379211426},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7122108936309814},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5787797570228577},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4823038578033447},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4690841734409332},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.41870853304862976},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4180241823196411},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3449578583240509}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9112458229064941},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7424893379211426},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7122108936309814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5787797570228577},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4823038578033447},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4690841734409332},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.41870853304862976},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4180241823196411},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3449578583240509}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1594587862","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W2095705004","https://openalex.org/W2097117768","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2168894214","https://openalex.org/W2194775991","https://openalex.org/W2274287116","https://openalex.org/W2302255633","https://openalex.org/W2401231614","https://openalex.org/W2406474429","https://openalex.org/W2563764042","https://openalex.org/W2950094539","https://openalex.org/W2962677625","https://openalex.org/W2962835968","https://openalex.org/W2963446712","https://openalex.org/W2964137095","https://openalex.org/W2964350391","https://openalex.org/W3118608800","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6684665197","https://openalex.org/W6730753511"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W3090555870","https://openalex.org/W3022820045","https://openalex.org/W2801655600","https://openalex.org/W3005627584","https://openalex.org/W4229443568"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,47,57,72,89],"achieve":[3],"higher":[4],"accuracy":[5],"of":[6,94,111],"image":[7],"recognition,":[8],"deeper":[9],"and":[10,98,113],"wider":[11],"networks":[12],"have":[13],"been":[14],"used.":[15],"However,":[16],"when":[17],"the":[18,48,79,103],"network":[19],"size":[20,110],"gets":[21],"bigger,":[22],"its":[23],"forward":[24,104],"inference":[25,105],"time":[26,106],"also":[27],"takes":[28,120],"longer.":[29],"To":[30],"address":[31],"this":[32],"problem,":[33],"we":[34],"propose":[35],"Deeply-Fused":[36],"Branchy":[37],"Network":[38],"(DFB-Net)":[39],"by":[40,68],"adding":[41],"small":[42],"but":[43],"complete":[44],"side":[45],"branches":[46],"target":[49],"baseline":[50],"main":[51],"branch.":[52],"DFB-Net":[53,64,85],"allows":[54],"easy-to-discriminate":[55],"samples":[56],"be":[58],"classified":[59],"faster.":[60],"For":[61],"hard-to-discriminate":[62],"samples,":[63],"makes":[65],"probability":[66],"fusion":[67],"averaging":[69],"softmax":[70],"probabilities":[71],"make":[73],"collaborative":[74],"predictions.":[75],"Extensive":[76],"experiments":[77],"on":[78,96,100,123,127],"two":[80],"CIFAR":[81],"datasets":[82],"show":[83],"that":[84],"achieves":[86],"state-of-the-art":[87],"results":[88],"obtain":[90],"an":[91],"error":[92],"rate":[93],"3.07%":[95],"CIFAR-10":[97],"16.01%":[99],"CIFAR-100.":[101],"Meanwhile,":[102],"(with":[107],"a":[108],"batch":[109],"1":[112],"averaged":[114],"among":[115],"all":[116],"test":[117],"samples)":[118],"only":[119],"10.4":[121],"ms":[122,126],"CIFAR-10,":[124],"18.8":[125],"CIFAR-100,":[128],"using":[129],"GTX":[130],"1080":[131],"GPU":[132],"with":[133],"cuDNN":[134],"5.1.":[135]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}