{"id":"https://openalex.org/W2789415215","doi":"https://doi.org/10.1109/icip.2017.8296359","title":"Batch-normalized recurrent highway networks","display_name":"Batch-normalized recurrent highway networks","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2789415215","doi":"https://doi.org/10.1109/icip.2017.8296359","mag":"2789415215"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296359","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":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1809.10271","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111265785","display_name":"Chi Zhang","orcid":"https://orcid.org/0009-0000-0323-0715"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chi Zhang","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101590296","display_name":"Thang Nguyen","orcid":"https://orcid.org/0009-0007-6659-9596"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thang Nguyen","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002928269","display_name":"Shagan Sah","orcid":"https://orcid.org/0000-0002-0388-9111"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shagan Sah","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032475867","display_name":"Raymond Ptucha","orcid":"https://orcid.org/0000-0002-2712-7429"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raymond Ptucha","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051767562","display_name":"Alexander C. Loui","orcid":"https://orcid.org/0000-0002-7427-1503"},"institutions":[{"id":"https://openalex.org/I4210159451","display_name":"Kodak (United States)","ror":"https://ror.org/04rn3ph18","country_code":"US","type":"company","lineage":["https://openalex.org/I4210159451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander Loui","raw_affiliation_strings":["Kodak Alaris Imaging Science R&D, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kodak Alaris Imaging Science R&D, Rochester, NY, USA","institution_ids":["https://openalex.org/I4210159451"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050289545","display_name":"Carl Salvaggio","orcid":"https://orcid.org/0000-0001-9293-9696"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carl Salvaggio","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1592,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.55779111,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"29","issue":null,"first_page":"640","last_page":"644"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9983000159263611,"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":0.9983000159263611,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9958000183105469,"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":0.9894999861717224,"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/jacobian-matrix-and-determinant","display_name":"Jacobian matrix and determinant","score":0.8060088157653809},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6988695859909058},{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.6960434317588806},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6663224697113037},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6403488516807556},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5077673196792603},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.48805415630340576},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.45592617988586426},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4494943618774414},{"id":"https://openalex.org/keywords/balanced-flow","display_name":"Balanced flow","score":0.44354182481765747},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4363349378108978},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4162040054798126},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3672104477882385},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.333027720451355},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3257913589477539},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.28213343024253845},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.19810444116592407},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1781197488307953},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10681134462356567}],"concepts":[{"id":"https://openalex.org/C200331156","wikidata":"https://www.wikidata.org/wiki/Q506041","display_name":"Jacobian matrix and determinant","level":2,"score":0.8060088157653809},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6988695859909058},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.6960434317588806},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6663224697113037},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6403488516807556},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5077673196792603},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.48805415630340576},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.45592617988586426},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4494943618774414},{"id":"https://openalex.org/C167879884","wikidata":"https://www.wikidata.org/wiki/Q727568","display_name":"Balanced flow","level":2,"score":0.44354182481765747},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4363349378108978},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4162040054798126},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3672104477882385},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.333027720451355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3257913589477539},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28213343024253845},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.19810444116592407},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1781197488307953},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10681134462356567},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2017.8296359","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296359","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"},{"id":"pmh:oai:arXiv.org:1809.10271","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.10271","pdf_url":"https://arxiv.org/pdf/1809.10271","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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:1809.10271","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.10271","pdf_url":"https://arxiv.org/pdf/1809.10271","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"id":"https://metadata.un.org/sdg/11","score":0.7300000190734863,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W581956982","https://openalex.org/W1689711448","https://openalex.org/W1836465849","https://openalex.org/W1861492603","https://openalex.org/W1889081078","https://openalex.org/W1889624880","https://openalex.org/W1938755728","https://openalex.org/W1956340063","https://openalex.org/W2064675550","https://openalex.org/W2101105183","https://openalex.org/W2123301721","https://openalex.org/W2154652894","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2284050935","https://openalex.org/W2326533993","https://openalex.org/W2331143823","https://openalex.org/W2439078092","https://openalex.org/W2463955103","https://openalex.org/W2473934411","https://openalex.org/W2949117887","https://openalex.org/W2949892913","https://openalex.org/W2951559648","https://openalex.org/W2962949994","https://openalex.org/W2963304263","https://openalex.org/W2963685250","https://openalex.org/W2963983719","https://openalex.org/W2964084166","https://openalex.org/W2964335273","https://openalex.org/W3098682680","https://openalex.org/W4294555862","https://openalex.org/W4300807082","https://openalex.org/W4302375066","https://openalex.org/W4394643672","https://openalex.org/W4394666973","https://openalex.org/W6639102338","https://openalex.org/W6678262379","https://openalex.org/W6682631176","https://openalex.org/W6719092668","https://openalex.org/W6898505805"],"related_works":["https://openalex.org/W4210416330","https://openalex.org/W2775506363","https://openalex.org/W3088136942","https://openalex.org/W4290852288","https://openalex.org/W2949362007","https://openalex.org/W4388893791","https://openalex.org/W4283207562","https://openalex.org/W2963177403","https://openalex.org/W2330246314","https://openalex.org/W2949522393"],"abstract_inverted_index":{"Gradient":[0],"control":[1,59],"plays":[2],"an":[3,64,92],"important":[4],"role":[5],"in":[6,63],"feed-forward":[7],"networks":[8,55,108],"applied":[9],"to":[10,42,58],"various":[11],"computer":[12],"vision":[13],"tasks.":[14],"Previous":[15],"work":[16],"has":[17],"shown":[18],"that":[19,102],"Recurrent":[20],"Highway":[21],"Networks":[22],"minimize":[23],"the":[24,36,39,45,60,71,80,103,116],"problem":[25],"of":[26,38],"vanishing":[27],"or":[28],"exploding":[29],"gradients.":[30],"They":[31],"achieve":[32],"this":[33,49],"by":[34,77],"setting":[35],"eigenvalues":[37],"temporal":[40],"Jacobian":[41],"1":[43],"across":[44],"time":[46],"steps.":[47],"In":[48],"work,":[50],"batch":[51,78,104],"normalized":[52,105],"recurrent":[53,106],"highway":[54,107],"are":[56],"proposed":[57,87],"gradient":[61],"flow":[62],"improved":[65],"way":[66],"for":[67],"network":[68],"convergence.":[69],"Specifically,":[70],"introduced":[72],"model":[73,88],"can":[74],"be":[75],"formed":[76],"normalizing":[79],"inputs":[81],"at":[82],"each":[83],"recurrence":[84],"loop.":[85],"The":[86],"is":[89],"tested":[90],"on":[91],"image":[93],"captioning":[94],"task":[95],"using":[96],"MSCOCO":[97],"dataset.":[98],"Experimental":[99],"results":[100],"indicate":[101],"converge":[109],"faster":[110],"and":[111,119],"performs":[112],"better":[113],"compared":[114],"with":[115],"traditional":[117],"LSTM":[118],"RHN":[120],"based":[121],"models.":[122]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
