{"id":"https://openalex.org/W3159876672","doi":"https://doi.org/10.1109/icpr48806.2021.9413316","title":"Visual Object Tracking in Drone Images with Deep Reinforcement Learning","display_name":"Visual Object Tracking in Drone Images with Deep Reinforcement Learning","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3159876672","doi":"https://doi.org/10.1109/icpr48806.2021.9413316","mag":"3159876672"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9413316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9413316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5004018128","display_name":"Derya Gozen","orcid":null},"institutions":[{"id":"https://openalex.org/I168864056","display_name":"Bilkent University","ror":"https://ror.org/02vh8a032","country_code":"TR","type":"education","lineage":["https://openalex.org/I168864056"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Derya Gozen","raw_affiliation_strings":["Bilkent University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bilkent University","institution_ids":["https://openalex.org/I168864056"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033116884","display_name":"Sedat \u00d6zer","orcid":"https://orcid.org/0000-0002-2069-3807"},"institutions":[{"id":"https://openalex.org/I168864056","display_name":"Bilkent University","ror":"https://ror.org/02vh8a032","country_code":"TR","type":"education","lineage":["https://openalex.org/I168864056"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Sedat Ozer","raw_affiliation_strings":["Bilkent University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bilkent University","institution_ids":["https://openalex.org/I168864056"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I168864056"],"apc_list":null,"apc_paid":null,"fwci":1.6229,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.89726312,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"10082","last_page":"10089"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.8294333219528198},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7609224319458008},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7383403182029724},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7184080481529236},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6687093377113342},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5365453362464905},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5210520625114441},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5180521011352539},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4657942056655884},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.44016093015670776},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.18104282021522522},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09563422203063965}],"concepts":[{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.8294333219528198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7609224319458008},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7383403182029724},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7184080481529236},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6687093377113342},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5365453362464905},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5210520625114441},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5180521011352539},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4657942056655884},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.44016093015670776},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.18104282021522522},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09563422203063965},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr48806.2021.9413316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9413316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.bilkent.edu.tr:11693/77132","is_oa":false,"landing_page_url":"http://hdl.handle.net/11693/77132","pdf_url":null,"source":{"id":"https://openalex.org/S4306400079","display_name":"Bilkent University Institutional Repository (Bilkent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I168864056","host_organization_name":"Bilkent University","host_organization_lineage":["https://openalex.org/I168864056"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Pattern Recognition","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1857884451","https://openalex.org/W1964846093","https://openalex.org/W2044986361","https://openalex.org/W2069741238","https://openalex.org/W2086677144","https://openalex.org/W2089961441","https://openalex.org/W2124211486","https://openalex.org/W2130026429","https://openalex.org/W2158592639","https://openalex.org/W2158827467","https://openalex.org/W2162383208","https://openalex.org/W2186330282","https://openalex.org/W2204874854","https://openalex.org/W2214352687","https://openalex.org/W2408241409","https://openalex.org/W2470394683","https://openalex.org/W2518013266","https://openalex.org/W2557641257","https://openalex.org/W2584265939","https://openalex.org/W2610871254","https://openalex.org/W2738318237","https://openalex.org/W2739381051","https://openalex.org/W2762926425","https://openalex.org/W2787941778","https://openalex.org/W2796919380","https://openalex.org/W2916150848","https://openalex.org/W2963173190","https://openalex.org/W2963854930","https://openalex.org/W2963979855","https://openalex.org/W2964242925","https://openalex.org/W2998802733","https://openalex.org/W3003605730","https://openalex.org/W3005051486","https://openalex.org/W3013759317","https://openalex.org/W3015505697","https://openalex.org/W3045174566","https://openalex.org/W6781378744"],"related_works":["https://openalex.org/W4229448053","https://openalex.org/W4247925126","https://openalex.org/W4327774218","https://openalex.org/W2059768187","https://openalex.org/W4312858960","https://openalex.org/W4386036939","https://openalex.org/W4379143281","https://openalex.org/W2605096541","https://openalex.org/W3200286695","https://openalex.org/W2965594636"],"abstract_inverted_index":{"There":[0],"is":[1,37,160],"an":[2,31,39,135],"increasing":[3],"demand":[4],"on":[5,74,110,214,269,279,291],"utilizing":[6],"camera":[7],"equipped":[8],"drones":[9],"and":[10,21,33,59,91,95,101,204,254,263,283,328],"their":[11],"applications":[12],"in":[13,139,155,200,261,266,289],"many":[14],"domains":[15],"varying":[16],"from":[17,22,250],"agriculture":[18],"to":[19,25,53,65,70,88,103,148,187,195,211,230,242,257,286,298,312,325],"entertainment":[20],"sports":[23],"events":[24],"surveillance.":[26],"In":[27,119],"such":[28],"drone":[29,75,111,140,175],"applications,":[30],"essential":[32],"a":[34,124,144,165,170,181,207,221,243],"common":[35],"task":[36],"tracking":[38,248],"object":[40,68,86,131,136,154,167],"of":[41,137,146,152,192,223,245,303,315],"interest":[42,138],"visually.":[43],"Drone":[44],"(or":[45],"UAV)":[46],"images":[47,58,112,141],"have":[48],"different":[49,93,99,208],"properties":[50],"when":[51,296],"compared":[52,297],"the":[54,66,116,150,153,156,161,189,197,201,227,234,246,251,270,292,299,304,310,316],"ground":[55],"taken":[56,194],"(natural)":[57],"those":[60,81],"differences":[61,79],"introduce":[62,123,220],"additional":[63,277],"complexities":[64,82],"existing":[67],"trackers":[69],"be":[71,89,104,212],"directly":[72],"applied":[73],"applications.":[76,118],"Some":[77],"important":[78],"among":[80],"include":[83],"(i)":[84],"smaller":[85],"sizes":[87],"tracked":[90],"(ii)":[92],"orientations":[94],"viewing":[96],"angles":[97],"yielding":[98],"texture":[100],"features":[102],"observed.":[105],"Therefore,":[106],"new":[107,224],"algorithms":[108],"trained":[109],"are":[113],"needed":[114],"for":[115,174,331],"drone-based":[117],"this":[120],"paper,":[121],"we":[122,219,308],"deep":[125,171],"reinforcement":[126],"learning":[127],"(RL)":[128],"based":[129],"single":[130,166],"tracker":[132,168],"that":[133,185],"tracks":[134],"by":[142],"estimating":[143],"series":[145],"actions":[147,193,225],"find":[149],"location":[151,199],"next":[157,202],"frame.":[158],"This":[159],"first":[162],"work":[163],"introducing":[164],"using":[169],"RL-based":[172],"technique":[173],"images.":[176,217],"Our":[177],"proposed":[178,240,333],"solution":[179],"introduces":[180,206],"novel":[182],"reward":[183],"function":[184],"aims":[186],"reduce":[188],"total":[190],"number":[191],"estimate":[196],"object's":[198],"frame":[203],"also":[205,275],"backbone":[209],"network":[210],"used":[213],"low":[215],"resolution":[216],"Additionally,":[218],"set":[222,282,295],"into":[226],"action":[228],"library":[229],"better":[231],"deal":[232],"with":[233],"above-mentioned":[235],"complexities.":[236],"We":[237,274],"compare":[238],"our":[239,332],"solutions":[241],"state":[244,302],"art":[247,305],"algorithm":[249],"recent":[252],"literature":[253],"demonstrate":[255],"up":[256,285],"3.87":[258],"%":[259],"improvement":[260,265,288],"precision":[262,290],"3.6%":[264],"IoU":[267],"values":[268],"VisDrone2019":[271],"data":[272,281,294],"set.":[273],"provide":[276],"results":[278],"OTB-100":[280,293],"show":[284],"3.15%":[287],"same":[300],"previous":[301],"algorithm.":[306],"Lastly,":[307],"analyze":[309],"ability":[311],"handle":[313],"some":[314],"challenges":[317],"faced":[318],"during":[319],"tracking,":[320],"including":[321],"but":[322],"not":[323],"limited":[324],"occlusion,":[326],"deformation,":[327],"scale":[329],"variation":[330],"solutions.":[334]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}