{"id":"https://openalex.org/W2588632739","doi":"https://doi.org/10.1109/dasip.2016.7853811","title":"A pipelined multi-softcore approach for the HOG algorithm","display_name":"A pipelined multi-softcore approach for the HOG algorithm","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2588632739","doi":"https://doi.org/10.1109/dasip.2016.7853811","mag":"2588632739"},"language":"en","primary_location":{"id":"doi:10.1109/dasip.2016.7853811","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dasip.2016.7853811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Conference on Design and Architectures for Signal and Image Processing (DASIP)","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/A5111443277","display_name":"Jose Arnaldo Mascagni de Holanda","orcid":null},"institutions":[{"id":"https://openalex.org/I107371206","display_name":"Federal Institute of S\u00e3o Paulo","ror":"https://ror.org/005pn5z34","country_code":"BR","type":"education","lineage":["https://openalex.org/I107371206"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Jose Arnaldo Mascagni de Holanda","raw_affiliation_strings":["Federal Institute of S\u00e3o Paulo, Brazil"],"affiliations":[{"raw_affiliation_string":"Federal Institute of S\u00e3o Paulo, Brazil","institution_ids":["https://openalex.org/I107371206"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007667456","display_name":"Jo\u00e3o M. P. Cardoso","orcid":"https://orcid.org/0000-0002-7353-1799"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Joao Manuel Paiva Cardoso","raw_affiliation_strings":["Universidade do Porto, Porto, Porto, PT"],"affiliations":[{"raw_affiliation_string":"Universidade do Porto, Porto, Porto, PT","institution_ids":["https://openalex.org/I182534213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032834863","display_name":"Eduardo Marques","orcid":"https://orcid.org/0000-0002-7747-3602"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Eduardo Marques","raw_affiliation_strings":["University of Sao Paulo, S??o Carlos, Brazil"],"affiliations":[{"raw_affiliation_string":"University of Sao Paulo, S??o Carlos, Brazil","institution_ids":["https://openalex.org/I17974374"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5111443277"],"corresponding_institution_ids":["https://openalex.org/I107371206"],"apc_list":null,"apc_paid":null,"fwci":0.3675,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.68227292,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"25","issue":null,"first_page":"146","last_page":"153"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.9975000023841858,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9969000220298767,"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/computer-science","display_name":"Computer science","score":0.8278437852859497},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.7571747303009033},{"id":"https://openalex.org/keywords/nios-ii","display_name":"Nios II","score":0.7012547254562378},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6981606483459473},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.5892772078514099},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5750730633735657},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.5362685322761536},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.5267189145088196},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.491430401802063},{"id":"https://openalex.org/keywords/multiprocessing","display_name":"Multiprocessing","score":0.473722368478775},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.4467315971851349},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.4396301209926605},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3665104806423187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.09782567620277405},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07632189989089966}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8278437852859497},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.7571747303009033},{"id":"https://openalex.org/C2781190120","wikidata":"https://www.wikidata.org/wiki/Q438281","display_name":"Nios II","level":3,"score":0.7012547254562378},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6981606483459473},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5892772078514099},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5750730633735657},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.5362685322761536},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.5267189145088196},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.491430401802063},{"id":"https://openalex.org/C4822641","wikidata":"https://www.wikidata.org/wiki/Q846651","display_name":"Multiprocessing","level":2,"score":0.473722368478775},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4467315971851349},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.4396301209926605},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3665104806423187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.09782567620277405},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07632189989089966},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","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":1,"locations":[{"id":"doi:10.1109/dasip.2016.7853811","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dasip.2016.7853811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Conference on Design and Architectures for Signal and Image Processing (DASIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1487718959","https://openalex.org/W1541157786","https://openalex.org/W1635597477","https://openalex.org/W1650122911","https://openalex.org/W1972535453","https://openalex.org/W1981182985","https://openalex.org/W1992914425","https://openalex.org/W2009295221","https://openalex.org/W2012424613","https://openalex.org/W2031454541","https://openalex.org/W2052533453","https://openalex.org/W2062130228","https://openalex.org/W2074091263","https://openalex.org/W2096112371","https://openalex.org/W2099355420","https://openalex.org/W2109330262","https://openalex.org/W2134800624","https://openalex.org/W2136964839","https://openalex.org/W2140093718","https://openalex.org/W2161969291","https://openalex.org/W2573758757","https://openalex.org/W3210232381","https://openalex.org/W6629152525","https://openalex.org/W6632503415","https://openalex.org/W6636787326","https://openalex.org/W6636893432","https://openalex.org/W6674636832","https://openalex.org/W6803376173"],"related_works":["https://openalex.org/W2120447654","https://openalex.org/W2977179488","https://openalex.org/W2144453115","https://openalex.org/W2128223750","https://openalex.org/W2182238953","https://openalex.org/W2146716617","https://openalex.org/W2385597935","https://openalex.org/W2335645676","https://openalex.org/W2399947648","https://openalex.org/W1998372059"],"abstract_inverted_index":{"This":[0],"paper":[1,100],"describes":[2],"the":[3,6,30,107,139,149,162],"mapping":[4],"and":[5,41,74,86,120,132],"acceleration":[7,152],"of":[8,25,29,36,39,51,76,88,130,158],"an":[9,19],"object":[10],"detection":[11,35],"algorithm":[12,78,109],"on":[13,18,53],"a":[14,111],"multiprocessor":[15],"system":[16],"based":[17],"FPGA.":[20],"We":[21,144],"use":[22,50],"HOG":[23,52,108],"(Histogram":[24],"Oriented":[26],"Gradients),":[27],"one":[28],"most":[31],"popular":[32],"algorithms":[33,140],"for":[34],"different":[37,84],"classes":[38,87],"objects":[40],"currently":[42],"being":[43],"used":[44],"in":[45,59,117,156],"smart":[46],"embedded":[47,163],"systems.":[48],"The":[49],"such":[54],"systems":[55],"requires":[56],"efficient":[57],"implementations":[58],"order":[60],"to":[61,81,93,161],"provide":[62],"high":[63],"performance":[64],"possibly":[65],"with":[66,83,151],"low":[67],"energy/power":[68],"consumption":[69],"budgets.":[70],"Also,":[71],"as":[72],"variations":[73],"adaptations":[75],"this":[77,99],"are":[79],"needed":[80],"deal":[82],"scenarios":[85],"objects,":[89],"programmability":[90,121],"is":[91],"required":[92],"allow":[94],"greater":[95],"development":[96],"flexibility.":[97],"In":[98],"we":[101,127,137],"show":[102,146],"our":[103],"approach":[104],"towards":[105],"implementing":[106],"into":[110],"multi-softcore":[112],"Nios":[113],"II":[114],"based-system,":[115],"bearing":[116],"mind":[118],"high-performance":[119],"issues.":[122],"By":[123],"applying":[124],"source-to-source":[125],"transformations":[126],"obtain":[128],"speedups":[129,157],"19\u00d7":[131],"by":[133],"using":[134],"pipelined":[135],"processing":[136],"reduce":[138],"execution":[141],"time":[142],"49\u00d7.":[143],"also":[145],"that":[147],"improving":[148],"hardware":[150],"units":[153],"can":[154],"result":[155],"72.4\u00d7":[159],"compared":[160],"baseline":[164],"application.":[165]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
