{"id":"https://openalex.org/W2735039185","doi":"https://doi.org/10.1109/vcip.2017.8305148","title":"LinkNet: Exploiting encoder representations for efficient semantic segmentation","display_name":"LinkNet: Exploiting encoder representations for efficient semantic segmentation","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2735039185","doi":"https://doi.org/10.1109/vcip.2017.8305148","mag":"2735039185"},"language":"en","primary_location":{"id":"doi:10.1109/vcip.2017.8305148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2017.8305148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1707.03718","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Abhishek Chaurasia","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abhishek Chaurasia","raw_affiliation_strings":["School of Electrical and Computer Engineering, Purdue University, West Lafayette, USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Purdue University, West Lafayette, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":null,"display_name":"Eugenio Culurciello","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eugenio Culurciello","raw_affiliation_strings":["Weldon School of Biomedical Engineering, Purdue University, West Lafayette, USA"],"affiliations":[{"raw_affiliation_string":"Weldon School of Biomedical Engineering, Purdue University, West Lafayette, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":20.7067,"has_fulltext":false,"cited_by_count":1410,"citation_normalized_percentile":{"value":0.99527137,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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":0.9998000264167786,"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":0.9997000098228455,"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/segmentation","display_name":"Segmentation","score":0.6995999813079834},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.6237000226974487},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6212999820709229},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5995000004768372},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5175999999046326},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5074999928474426},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4399000108242035},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.40450000762939453}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8255000114440918},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6995999813079834},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.6237000226974487},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6212999820709229},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6187999844551086},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5995000004768372},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5175999999046326},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5074999928474426},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5019000172615051},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4399000108242035},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.40450000762939453},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3878999948501587},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3695000112056732},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.31850001215934753},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3043999969959259},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2721000015735626},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C106515295","wikidata":"https://www.wikidata.org/wiki/Q26806595","display_name":"Parallel processing","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C98025372","wikidata":"https://www.wikidata.org/wiki/Q477538","display_name":"Systems architecture","level":3,"score":0.2542000114917755}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/vcip.2017.8305148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2017.8305148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1707.03718","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1707.03718","pdf_url":"https://arxiv.org/pdf/1707.03718","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1707.03718","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1707.03718","pdf_url":"https://arxiv.org/pdf/1707.03718","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1745334888","https://openalex.org/W1903029394","https://openalex.org/W1905829557","https://openalex.org/W1913356549","https://openalex.org/W1936750108","https://openalex.org/W2022508996","https://openalex.org/W2097117768","https://openalex.org/W2124592697","https://openalex.org/W2139427956","https://openalex.org/W2340897893","https://openalex.org/W2963037989","https://openalex.org/W2963166928","https://openalex.org/W4238404964","https://openalex.org/W4244914727","https://openalex.org/W6622239757","https://openalex.org/W6632100814","https://openalex.org/W6637242042","https://openalex.org/W6666899075","https://openalex.org/W6684191040","https://openalex.org/W6686207219"],"related_works":[],"abstract_inverted_index":{"Pixel-wise":[0],"semantic":[1],"segmentation":[2],"for":[3,95,136],"visual":[4],"scene":[5],"understanding":[6],"not":[7,34],"only":[8,88],"needs":[9],"to":[10,18,75],"be":[11],"accurate,":[12],"but":[13,31],"also":[14,119],"efficient":[15],"in":[16,22,50,81],"order":[17],"find":[19],"any":[20,78],"use":[21],"real-time":[23],"application.":[24],"Existing":[25],"algorithms":[26],"even":[27],"though":[28],"are":[29,48],"accurate":[30],"they":[32,47],"do":[33],"focus":[35],"on":[36,110,115,125],"utilizing":[37],"the":[38],"parameters":[39,53,91],"of":[40,52,56,83,99],"neural":[41,69],"network":[42,70,86],"efficiently.":[43],"As":[44],"a":[45,66],"result":[46],"huge":[49],"terms":[51],"and":[54,92,112,128],"number":[55,82],"operations;":[57],"hence":[58],"slow":[59],"too.":[60],"In":[61],"this":[62],"paper,":[63],"we":[64],"propose":[65],"novel":[67],"deep":[68],"architecture":[71],"which":[72],"allows":[73],"it":[74],"learn":[76],"without":[77],"significant":[79],"increase":[80],"parameters.":[84],"Our":[85],"uses":[87],"11.5":[89],"million":[90],"21.2":[93],"GFLOPs":[94],"processing":[96,123],"an":[97],"image":[98,138],"resolution":[100],"3":[101],"\u00d7":[102,104],"640":[103],"360.":[105],"It":[106],"gives":[107],"state-of-the-art":[108,134],"performance":[109],"CamVid":[111],"comparable":[113],"results":[114],"Cityscapes":[116],"dataset.":[117],"We":[118],"compare":[120],"our":[121],"networks":[122],"time":[124],"NVIDIA":[126],"GPU":[127],"embedded":[129],"system":[130],"device":[131],"with":[132],"existing":[133],"architectures":[135],"different":[137],"resolutions.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":41},{"year":2025,"cited_by_count":218},{"year":2024,"cited_by_count":271},{"year":2023,"cited_by_count":238},{"year":2022,"cited_by_count":253},{"year":2021,"cited_by_count":165},{"year":2020,"cited_by_count":132},{"year":2019,"cited_by_count":75},{"year":2018,"cited_by_count":17}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2017-07-21T00:00:00"}