{"id":"https://openalex.org/W4210906705","doi":"https://doi.org/10.1080/08839514.2022.2031825","title":"Intelligent System Utilizing HOG and CNN for Thermal Image-Based Detection of Wild Animals in Nocturnal Periods for Vehicle Safety","display_name":"Intelligent System Utilizing HOG and CNN for Thermal Image-Based Detection of Wild Animals in Nocturnal Periods for Vehicle Safety","publication_year":2022,"publication_date":"2022-02-08","ids":{"openalex":"https://openalex.org/W4210906705","doi":"https://doi.org/10.1080/08839514.2022.2031825"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2022.2031825","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2031825","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2031825?needAccess=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2031825?needAccess=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076478756","display_name":"Yuvaraj Munian","orcid":"https://orcid.org/0000-0002-5410-0037"},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuvaraj Munian","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at San Antonio (Utsa), San Antonio, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at San Antonio (Utsa), San Antonio, Texas, USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087956656","display_name":"Antonio Mart\u00ednez-Molina","orcid":"https://orcid.org/0000-0002-3937-7329"},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Antonio Martinez-Molina","raw_affiliation_strings":["School of Architecture and Design, the University of Texas at San Antonio (Utsa), San Antonio, Texas, USA"],"affiliations":[{"raw_affiliation_string":"School of Architecture and Design, the University of Texas at San Antonio (Utsa), San Antonio, Texas, USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050257768","display_name":"Dimitrios Miserlis","orcid":"https://orcid.org/0000-0002-2407-4552"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dimitrios Miserlis","raw_affiliation_strings":["Department of Surgery \u2013 Vascular Surgery, The University of Texas \u2013 Health Sciences Center, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Surgery \u2013 Vascular Surgery, The University of Texas \u2013 Health Sciences Center, Texas, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016578491","display_name":"Hermilo Hern\u00e1ndez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hermilo Hernandez","raw_affiliation_strings":["25:2 Solutions Corporation, Pocatello, Idaho USA"],"affiliations":[{"raw_affiliation_string":"25:2 Solutions Corporation, Pocatello, Idaho USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074118906","display_name":"Miltiadis Alamaniotis","orcid":"https://orcid.org/0000-0003-0787-5013"},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Miltiadis Alamaniotis","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at San Antonio (Utsa), San Antonio, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at San Antonio (Utsa), San Antonio, Texas, USA","institution_ids":["https://openalex.org/I45438204"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5074118906"],"corresponding_institution_ids":["https://openalex.org/I45438204"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":{"value":2195,"currency":"USD","value_usd":2195},"fwci":4.5946,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.94764186,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"36","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12644","display_name":"Wildlife-Road Interactions and Conservation","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12644","display_name":"Wildlife-Road Interactions and Conservation","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10199","display_name":"Wildlife Ecology and Conservation","score":0.9805999994277954,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12894","display_name":"Date Palm Research Studies","score":0.9732000231742859,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7807196378707886},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.708005428314209},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.6696498990058899},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6648172736167908},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6627634167671204},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5530708432197571},{"id":"https://openalex.org/keywords/adverse-weather","display_name":"Adverse weather","score":0.5227323174476624},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5179609060287476},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4836207926273346},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4288754463195801},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4220763146877289},{"id":"https://openalex.org/keywords/visibility","display_name":"Visibility","score":0.4195975661277771},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34333592653274536},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21464979648590088}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7807196378707886},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.708005428314209},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.6696498990058899},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6648172736167908},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6627634167671204},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5530708432197571},{"id":"https://openalex.org/C2992147540","wikidata":"https://www.wikidata.org/wiki/Q1277161","display_name":"Adverse weather","level":2,"score":0.5227323174476624},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5179609060287476},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4836207926273346},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4288754463195801},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4220763146877289},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.4195975661277771},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34333592653274536},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21464979648590088},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2022.2031825","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2031825","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2031825?needAccess=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e67f8c0819064451bb7884c76c651f06","is_oa":true,"landing_page_url":"https://doaj.org/article/e67f8c0819064451bb7884c76c651f06","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 36, Iss 1 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/08839514.2022.2031825","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2031825","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2031825?needAccess=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5799999833106995,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4210906705.pdf","grobid_xml":"https://content.openalex.org/works/W4210906705.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1965484410","https://openalex.org/W1999621311","https://openalex.org/W2063988658","https://openalex.org/W2099355420","https://openalex.org/W2129335020","https://openalex.org/W2151103935","https://openalex.org/W2161969291","https://openalex.org/W2401150027","https://openalex.org/W2417429787","https://openalex.org/W2533302542","https://openalex.org/W2567289819","https://openalex.org/W2611953050","https://openalex.org/W2614851820","https://openalex.org/W2618695522","https://openalex.org/W2763838557","https://openalex.org/W2886495409","https://openalex.org/W2887887897","https://openalex.org/W2893442230","https://openalex.org/W2906257585","https://openalex.org/W2912130719","https://openalex.org/W2954038496","https://openalex.org/W2964298670","https://openalex.org/W2971562016","https://openalex.org/W2973613996","https://openalex.org/W2980488414","https://openalex.org/W2988600867","https://openalex.org/W2988648371","https://openalex.org/W3001083904","https://openalex.org/W3011696708","https://openalex.org/W3042012562","https://openalex.org/W3110932429","https://openalex.org/W3157645661","https://openalex.org/W3185094381","https://openalex.org/W4247114672"],"related_works":["https://openalex.org/W4321636153","https://openalex.org/W2779573348","https://openalex.org/W1995536880","https://openalex.org/W4377964522","https://openalex.org/W4210781881","https://openalex.org/W2620723295","https://openalex.org/W4255221925","https://openalex.org/W3195168932","https://openalex.org/W4386072274","https://openalex.org/W4386123260"],"abstract_inverted_index":{"Animal":[0],"Vehicle":[1],"Collision,":[2],"commonly":[3],"called":[4],"roadkill,":[5],"is":[6,87],"an":[7,59],"emerging":[8],"threat":[9],"to":[10,41],"drivers":[11],"and":[12,97,100,123],"wild":[13,160,176],"animals,":[14],"increasing":[15],"fatalities":[16],"every":[17],"year.":[18],"Currently,":[19],"prevalent":[20],"methods":[21],"using":[22],"visible":[23],"light":[24],"cameras":[25],"are":[26],"efficient":[27],"for":[28,62],"animal":[29,63],"detection":[30,64,130,173],"in":[31,148],"daylight":[32],"time.":[33],"This":[34],"paper":[35],"focuses":[36],"on":[37,134,145,178],"locating":[38],"wildlife":[39],"close":[40],"roads":[42],"during":[43,65],"nocturnal":[44],"hours":[45],"by":[46],"utilizing":[47],"thermographic":[48],"obtained":[49],"images,":[50],"thus":[51],"enhancing":[52],"vehicle":[53],"safety.":[54],"In":[55],"particular,":[56],"it":[57,181],"proposes":[58],"intelligent":[60,85],"system":[61,86,131],"nighttime":[66],"that":[67,156,165],"combines":[68],"the":[69,103,146,149,166,183,186],"technique":[70],"of":[71,73,92,137,151,159,175,185],"Histogram":[72],"Oriented":[74],"Gradients":[75],"(HOG)":[76],"with":[77,102,141],"a":[78,90,135,142],"Convolutional":[79],"Neural":[80],"Network":[81],"(CNN).":[82],"The":[83,128],"proposed":[84,129],"benchmarked":[88],"against":[89],"variety":[91],"CNN\u2019s":[93],"like":[94],"basic":[95],"CNN":[96,99],"VGG16-based":[98],"also":[101],"machine":[104,188],"learning":[105,189],"algorithms":[106],"such":[107],"as":[108],"Support":[109],"Vector":[110],"Machine":[111],"(SVM),":[112],"Random":[113],"Forest":[114],"(RF),":[115],"Decision":[116],"Tree":[117],"Algorithm":[118],"(DT),":[119],"Linear":[120],"Regression":[121],"(LR),":[122],"Gaussian":[124],"Na\u00efve":[125],"Bayes":[126],"(GNB).":[127],"was":[132],"tested":[133,187],"set":[136],"real-world":[138],"data":[139],"acquired":[140],"thermal":[143],"camera":[144],"move":[147],"city":[150],"San":[152],"Antonio,":[153],"TX,":[154],"USA":[155],"includes":[157],"images":[158],"deer.":[161],"Obtained":[162],"results":[163],"exhibit":[164],"HOG-CNN":[167],"combination":[168],"achieved":[169],"approximately":[170],"91%":[171],"correct":[172],"accuracy":[174],"deer":[177],"roadsides,":[179],"while":[180],"outperformed":[182],"rest":[184],"algorithms.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}