{"id":"https://openalex.org/W2813431130","doi":"https://doi.org/10.1145/3200947.3201024","title":"Recurrent Attention for Deep Neural Object Detection","display_name":"Recurrent Attention for Deep Neural Object Detection","publication_year":2018,"publication_date":"2018-07-06","ids":{"openalex":"https://openalex.org/W2813431130","doi":"https://doi.org/10.1145/3200947.3201024","mag":"2813431130"},"language":"en","primary_location":{"id":"doi:10.1145/3200947.3201024","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3200947.3201024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th Hellenic Conference on Artificial Intelligence","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/A5079933694","display_name":"Georgios Symeonidis","orcid":"https://orcid.org/0000-0002-3380-0819"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Georgios Symeonidis","raw_affiliation_strings":["Aristotle University of Thessaloniki, Department of Informatics"],"affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki, Department of Informatics","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041054091","display_name":"Anastasios Tefas","orcid":"https://orcid.org/0000-0003-1288-3667"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Anastasios Tefas","raw_affiliation_strings":["Aristotle University of Thessaloniki, Department of Informatics"],"affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki, Department of Informatics","institution_ids":["https://openalex.org/I21370196"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5079933694"],"corresponding_institution_ids":["https://openalex.org/I21370196"],"apc_list":null,"apc_paid":null,"fwci":0.3134,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.61267464,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9979000091552734,"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":0.9970999956130981,"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":0.8269903659820557},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7639948129653931},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7252577543258667},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5821307897567749},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5713828802108765},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5617504119873047},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5344613790512085},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5284625887870789},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5276110172271729},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5072752833366394},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5053401589393616},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.4399494230747223},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3527507781982422},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07144463062286377}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8269903659820557},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7639948129653931},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7252577543258667},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5821307897567749},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5713828802108765},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5617504119873047},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5344613790512085},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5284625887870789},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5276110172271729},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5072752833366394},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5053401589393616},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.4399494230747223},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3527507781982422},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07144463062286377},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3200947.3201024","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3200947.3201024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th Hellenic Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W7746136","https://openalex.org/W1514535095","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W2031489346","https://openalex.org/W2064675550","https://openalex.org/W2088049833","https://openalex.org/W2100649405","https://openalex.org/W2102605133","https://openalex.org/W2107878631","https://openalex.org/W2122585011","https://openalex.org/W2193145675","https://openalex.org/W2216125271","https://openalex.org/W2546781373","https://openalex.org/W2612135493","https://openalex.org/W2618530766","https://openalex.org/W2951912364","https://openalex.org/W2952020226","https://openalex.org/W2953106684","https://openalex.org/W3106250896","https://openalex.org/W3122238731","https://openalex.org/W4212774754"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2949096641","https://openalex.org/W2969228573","https://openalex.org/W2970686063","https://openalex.org/W4320729701"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,113,193],"deep":[3,19,99],"learning":[4],"have":[5],"achieved":[6],"state-of-the-art":[7],"results":[8],"for":[9,78,102,130,140,166,185],"object":[10,50,103,117],"detection":[11,16,51,133],"by":[12,82],"replacing":[13],"the":[14,33,60,65,74,85,90,107,110,114,162,181,194,198,201],"traditional":[15],"methodologies":[17],"with":[18],"convolutional":[20],"neural":[21,46,100],"network":[22],"architectures.":[23],"A":[24],"contemporary":[25],"technique":[26],"that":[27,105,126,160,179],"is":[28,52,121],"shown":[29],"to":[30,49,72,122,176],"further":[31],"improve":[32,73],"performance":[34,199],"of":[35,89,109,200],"these":[36],"models":[37],"on":[38,54,84],"tasks":[39],"ranging":[40],"from":[41],"optical":[42],"character":[43],"recognition":[44,104],"and":[45,68,149,169],"machine":[47],"translation":[48],"based":[53],"incorporating":[55],"an":[56],"attention":[57,66,111,124],"mechanism":[58,67,112],"within":[59],"models.":[61],"The":[62,119,152,188],"idea":[63,108],"behind":[64],"its":[69],"variations":[70],"was":[71],"information":[75],"quality":[76],"extracted":[77],"any":[79],"confronted":[80],"task":[81],"focusing":[83],"most":[86],"relevant":[87],"parts":[88],"input.":[91],"In":[92],"this":[93],"paper":[94],"we":[95],"propose":[96],"two":[97],"novel":[98],"architectures":[101],"incorporate":[106],"well-known":[115],"faster-RCNN":[116,203],"detector.":[118],"objective":[120],"develop":[123],"mechanisms":[125],"can":[127],"be":[128],"used":[129],"small":[131],"objects":[132],"as":[134],"they":[135],"appear":[136],"when":[137],"using":[138],"Drones":[139],"covering":[141],"sport":[142],"events":[143],"like":[144],"bicycle":[145],"races,":[146],"football":[147],"matches":[148],"rowing":[150],"races.":[151],"proposed":[153,189],"approaches":[154],"include":[155,177],"a":[156,170],"class":[157,171],"agnostic":[158],"method":[159,173],"applies":[161],"same":[163],"predetermined":[164],"context":[165,178],"every":[167],"class,":[168],"specific":[172],"which":[174],"learns":[175],"maximizes":[180],"class's":[182],"precision":[183],"individually":[184],"each":[186],"class.":[187],"methods":[190],"are":[191],"evaluated":[192],"VOC2007":[195],"dataset,":[196],"improving":[197],"baseline":[202],"architecture.":[204]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
