{"id":"https://openalex.org/W2985875393","doi":"https://doi.org/10.1109/fpl.2019.00072","title":"An FPGA Implementation of Real-Time Object Detection with a Thermal Camera","display_name":"An FPGA Implementation of Real-Time Object Detection with a Thermal Camera","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2985875393","doi":"https://doi.org/10.1109/fpl.2019.00072","mag":"2985875393"},"language":"en","primary_location":{"id":"doi:10.1109/fpl.2019.00072","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fpl.2019.00072","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 29th International Conference on Field Programmable Logic and Applications (FPL)","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/A5043084588","display_name":"Masayuki Shimoda","orcid":"https://orcid.org/0000-0003-4627-0957"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Masayuki Shimoda","raw_affiliation_strings":["Tokyo Institute of Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089957553","display_name":"Youki Sada","orcid":null},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Youki Sada","raw_affiliation_strings":["Tokyo Institute of Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001468686","display_name":"Ryosuke Kuramochi","orcid":null},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryosuke Kuramochi","raw_affiliation_strings":["Tokyo Institute of Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070734898","display_name":"Hiroki Nakahara","orcid":"https://orcid.org/0000-0002-5701-7466"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroki Nakahara","raw_affiliation_strings":["Tokyo Institute of Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5043084588"],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":null,"apc_paid":null,"fwci":0.8098,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.77664723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"413","last_page":"414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9957000017166138,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9944999814033508,"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/detector","display_name":"Detector","score":0.7883332967758179},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7519172430038452},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7338565587997437},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6926764845848083},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6748870015144348},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6733068227767944},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6296331882476807},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.5728403925895691},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.554313063621521},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.47761887311935425},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.43062007427215576},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2456987202167511},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.12727153301239014},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12638461589813232},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06567728519439697}],"concepts":[{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.7883332967758179},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7519172430038452},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7338565587997437},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6926764845848083},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6748870015144348},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6733068227767944},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6296331882476807},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.5728403925895691},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.554313063621521},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.47761887311935425},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.43062007427215576},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2456987202167511},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.12727153301239014},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12638461589813232},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06567728519439697}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fpl.2019.00072","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fpl.2019.00072","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 29th International Conference on Field Programmable Logic and Applications (FPL)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2570343428","https://openalex.org/W2765493912","https://openalex.org/W2767018766","https://openalex.org/W2913269858","https://openalex.org/W2926066262","https://openalex.org/W3106250896","https://openalex.org/W6745521722","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W2355315220","https://openalex.org/W4200391368","https://openalex.org/W2210979487","https://openalex.org/W2074043759","https://openalex.org/W2316202402","https://openalex.org/W4293226380","https://openalex.org/W4225949190","https://openalex.org/W2969228573","https://openalex.org/W2963690996"],"abstract_inverted_index":{"We":[0],"demonstrate":[1],"a":[2,8,62,106,127,201,212,236],"sparse":[3,213],"YOLOv2-based":[4,214],"object":[5,47,66,89,109,195,204],"detector":[6,90,196,242],"with":[7,91],"thermal":[9,12,29,51,82,229],"camera.":[10],"A":[11],"camera":[13,52],"outputs":[14],"pixel":[15],"values":[16],"which":[17],"represent":[18],"heat":[19],"(temperature),":[20],"and":[21,68,105,129,132,137,153,161,227,243],"the":[22,28,38,50,81,84,88,113,140,144,156,175,185,190,225,228],"output":[23],"is":[24,37,53,60,74,146,187,197],"gray-scale":[25],"images.":[26],"Since":[27],"cameras":[30],"do":[31],"not":[32,41],"depend":[33],"on":[34,112,169,178,247],"whether":[35],"there":[36],"light":[39],"or":[40],"unlike":[42],"other":[43],"visible":[44],"range":[45],"cameras,":[46],"detection":[48,152],"using":[49],"reliable":[54,194,203],"without":[55],"ambient":[56],"surrounding.":[57],"This":[58],"topic":[59],"of":[61,87,108,126,143,167,184,192,211,223],"broad":[63],"interest":[64],"in":[65],"surveillance":[67],"action":[69],"recognition.":[70],"However,":[71],"since":[72],"it":[73,148],"challenging":[75],"to":[76,150],"extract":[77],"informative":[78],"features":[79],"from":[80],"images,":[83,182],"implementation":[85,168,210],"challenges":[86],"high":[92],"accuracy":[93],"remain.":[94],"In":[95,231],"recent":[96],"works,":[97],"convolutional":[98],"neural":[99],"networks":[100,120,177],"(CNNs)":[101],"outperform":[102],"conventional":[103],"techniques,":[104],"variety":[107],"detectors":[110,123],"based":[111],"CNNs":[114],"have":[115],"been":[116],"proposed.":[117],"The":[118],"representative":[119],"are":[121,218],"single-shot":[122],"that":[124,147,221],"consist":[125,222],"CNN":[128],"infer":[130],"locations":[131],"classes":[133],"simultaneously":[134],"(e.g.,":[135],"SSD":[136],"YOLOv2).":[138],"Although":[139],"primary":[141],"advantage":[142],"type":[145],"enables":[149],"train":[151],"classification":[154],"simultaneously,":[155],"resulting":[157],"increased":[158],"computation":[159],"time":[160],"area":[162],"requirements":[163],"can":[164],"cause":[165],"problems":[166,186],"an":[170,208,240],"FPGA.":[171],"Also,":[172],"as":[173],"for":[174],"proposed":[176,245],"RGB":[179,226],"three":[180],"channel":[181],"one":[183,215,246],"false":[188],"positive;":[189],"realization":[191],"more":[193],"required.":[198],"To":[199],"realize":[200],"real-time":[202],"detector,":[205],"we":[206,234],"investigate":[207],"FPGA":[209],"whose":[216],"inputs":[217],"four-channel":[219],"images":[220],"both":[224],"ones.":[230],"this":[232],"demonstration,":[233],"show":[235],"performance":[237],"comparison":[238],"between":[239],"RGB-based":[241],"our":[244],"FPGAs.":[248]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
