{"id":"https://openalex.org/W7124595731","doi":"https://doi.org/10.1007/s10846-025-02336-y","title":"FCN-Pose: A Pruned and Quantized CNN for Robot Pose Estimation for Constrained Devices","display_name":"FCN-Pose: A Pruned and Quantized CNN for Robot Pose Estimation for Constrained Devices","publication_year":2026,"publication_date":"2026-01-17","ids":{"openalex":"https://openalex.org/W7124595731","doi":"https://doi.org/10.1007/s10846-025-02336-y"},"language":"en","primary_location":{"id":"doi:10.1007/s10846-025-02336-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10846-025-02336-y","pdf_url":null,"source":{"id":"https://openalex.org/S91329792","display_name":"Journal of Intelligent & Robotic Systems","issn_l":"0921-0296","issn":["0921-0296","1573-0409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Robotic Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/s10846-025-02336-y","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084112841","display_name":"Marrone Dantas","orcid":null},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Marrone Silv\u00e9rio Melo Dantas","raw_affiliation_strings":["Federal University of Pernambuco, CIN, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","Federal University of Pernambuco, GPRT, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-7927-8472","affiliations":[{"raw_affiliation_string":"Federal University of Pernambuco, CIN, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","institution_ids":["https://openalex.org/I25112270"]},{"raw_affiliation_string":"Federal University of Pernambuco, GPRT, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011682830","display_name":"Assis T. de Oliveira Filho","orcid":null},"institutions":[{"id":"https://openalex.org/I221977067","display_name":"Universidade Cat\u00f3lica de Pernambuco","ror":"https://ror.org/02ktfmz27","country_code":"BR","type":"education","lineage":["https://openalex.org/I221977067"]},{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Assis T. de Oliveira Filho","raw_affiliation_strings":["Federal University of Pernambuco, CIN, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","Federal University of Pernambuco, GPRT, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","UNICAP, Catholic University of Pernambuco, R. do Pr\u00edncipe, 526 - Boa Vista, Recife, 50050-900, Pernambuco, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Pernambuco, CIN, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","institution_ids":["https://openalex.org/I25112270"]},{"raw_affiliation_string":"Federal University of Pernambuco, GPRT, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","institution_ids":["https://openalex.org/I25112270"]},{"raw_affiliation_string":"UNICAP, Catholic University of Pernambuco, R. do Pr\u00edncipe, 526 - Boa Vista, Recife, 50050-900, Pernambuco, Brazil","institution_ids":["https://openalex.org/I221977067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014967408","display_name":"Djamel Sadok","orcid":null},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Djamel Fawzi Hadj Sadok","raw_affiliation_strings":["Federal University of Pernambuco, CIN, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","Federal University of Pernambuco, GPRT, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Pernambuco, CIN, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","institution_ids":["https://openalex.org/I25112270"]},{"raw_affiliation_string":"Federal University of Pernambuco, GPRT, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007480342","display_name":"Judith Kelner","orcid":null},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Judith Kelner","raw_affiliation_strings":["Federal University of Pernambuco, CIN, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","Federal University of Pernambuco, GPRT, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Pernambuco, CIN, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","institution_ids":["https://openalex.org/I25112270"]},{"raw_affiliation_string":"Federal University of Pernambuco, GPRT, Cidade Universit\u00e1ria, Recife, 50670901, Pernambuco, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100372621","display_name":"Ricardo Silva","orcid":null},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Ricardo Silva","raw_affiliation_strings":["Ericsson, Ericsson Research, Rodovia Engenheiro Erm\u00eanio de Oliveira Penteado, Indaiatuba, 13337300, S\u00e3o Paulo, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson, Ericsson Research, Rodovia Engenheiro Erm\u00eanio de Oliveira Penteado, Indaiatuba, 13337300, S\u00e3o Paulo, Brazil","institution_ids":["https://openalex.org/I1306339040"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5084112841"],"corresponding_institution_ids":["https://openalex.org/I25112270"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11329569,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"112","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.25270000100135803,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10653","display_name":"Robot Manipulation and Learning","score":0.25270000100135803,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10036","display_name":"Advanced Neural Network Applications","score":0.15780000388622284,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.12479999661445618,"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/pruning","display_name":"Pruning","score":0.6579999923706055},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6259999871253967},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.6258999705314636},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5475999712944031},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5133000016212463},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.460099995136261},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4512999951839447},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4456999897956848},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.4002000093460083}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7045000195503235},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7038999795913696},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6579999923706055},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6259999871253967},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.6258999705314636},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5537999868392944},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5475999712944031},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5133000016212463},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4512999951839447},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4456999897956848},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.4002000093460083},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3612000048160553},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.35280001163482666},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.34610000252723694},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3156000077724457},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3127000033855438},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29269999265670776},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2551000118255615},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.25189998745918274},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10846-025-02336-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10846-025-02336-y","pdf_url":null,"source":{"id":"https://openalex.org/S91329792","display_name":"Journal of Intelligent & Robotic Systems","issn_l":"0921-0296","issn":["0921-0296","1573-0409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Robotic Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10846-025-02336-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10846-025-02336-y","pdf_url":null,"source":{"id":"https://openalex.org/S91329792","display_name":"Journal of Intelligent & Robotic Systems","issn_l":"0921-0296","issn":["0921-0296","1573-0409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Robotic Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320997","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","ror":"https://ror.org/02ddkpn78"},{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320323678","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Ci\u00eancia e Tecnologia do Estado de Pernambuco","ror":"https://ror.org/02te5rf52"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W28635149","https://openalex.org/W1902150074","https://openalex.org/W1903029394","https://openalex.org/W2023135124","https://openalex.org/W2025713906","https://openalex.org/W2059647426","https://openalex.org/W2080760147","https://openalex.org/W2097533491","https://openalex.org/W2112796928","https://openalex.org/W2150593711","https://openalex.org/W2233116163","https://openalex.org/W2546536770","https://openalex.org/W2618530766","https://openalex.org/W2618852836","https://openalex.org/W2799197246","https://openalex.org/W2890612125","https://openalex.org/W2933543903","https://openalex.org/W2955813853","https://openalex.org/W2963521844","https://openalex.org/W2963728985","https://openalex.org/W2964309882","https://openalex.org/W2971533524","https://openalex.org/W2980721699","https://openalex.org/W2981630388","https://openalex.org/W2996328914","https://openalex.org/W2998218113","https://openalex.org/W3005409765","https://openalex.org/W3012223454","https://openalex.org/W3013375890","https://openalex.org/W3022674470","https://openalex.org/W3035160371","https://openalex.org/W3045471054","https://openalex.org/W3047243383","https://openalex.org/W3081179222","https://openalex.org/W3090564508","https://openalex.org/W3095829752","https://openalex.org/W3097217077","https://openalex.org/W3097807933","https://openalex.org/W3159216148","https://openalex.org/W3160474996","https://openalex.org/W3166238888","https://openalex.org/W3203451691","https://openalex.org/W3210040340","https://openalex.org/W3211543249","https://openalex.org/W4210536149","https://openalex.org/W4224001196","https://openalex.org/W4281714038","https://openalex.org/W4294599671","https://openalex.org/W4309858908","https://openalex.org/W4313415362","https://openalex.org/W4367046413","https://openalex.org/W4379511033","https://openalex.org/W4387350746","https://openalex.org/W4393115925","https://openalex.org/W4399772304","https://openalex.org/W4401726555","https://openalex.org/W4402226173","https://openalex.org/W4404293984","https://openalex.org/W4405783794","https://openalex.org/W4409047846","https://openalex.org/W4414677386"],"related_works":[],"abstract_inverted_index":{"IoT":[0],"devices":[1],"are":[2],"a":[3,84,91,140,145,153,195,220,231,250,296],"technology":[4],"recurrent":[5],"in":[6,68,152,228,234],"the":[7,78,99,111,115,119,129,132,137,150,162,170,175,179,183,201,210,215,238,243,269,280],"contexts":[8],"of":[9,81,102,122,131,164,172,177,185,292],"Industry":[10],"4.0":[11],"and":[12,25,54,104,109,148,155,182,230],"real-time":[13],"applications.":[14],"Nonetheless,":[15],"they":[16],"suffer":[17],"from":[18,262,275],"resource":[19],"limitations,":[20],"such":[21,37],"as":[22,38],"processor,":[23],"RAM,":[24],"disc":[26,244],"storage.":[27],"These":[28],"limitations":[29],"become":[30],"more":[31],"evident":[32],"when":[33,278],"handling":[34],"demanding":[35],"applications,":[36],"deep":[39,60],"learning,":[40],"which":[41],"is":[42,57,70],"well-known":[43],"for":[44,94,125,144,205,242,268],"its":[45,64],"heavy":[46],"computational":[47],"requirements.":[48],"One":[49],"way":[50],"to":[51,106,219,265,283],"mitigate":[52],"processing":[53,261,273,290],"storage":[55,245],"problems":[56],"compressing":[58],"that":[59,76],"learning":[61],"application,":[62],"reducing":[63],"demands.":[65],"A":[66],"case":[67],"point":[69,254],"robot":[71],"pose":[72,95,141],"estimation,":[73],"an":[74,225],"application":[75],"predicts":[77],"critical":[79],"points":[80],"interest":[82],"on":[83],"desired":[85],"image":[86,203,260,293],"object.":[87],"This":[88,256],"paper":[89],"proposes":[90],"new":[92],"CNN":[93],"estimation":[96,142],"while":[97,246],"applying":[98],"compression":[100],"techniques":[101],"pruning":[103,116,222],"quantization":[105,127],"reduce":[107],"demands":[108],"improve":[110],"response":[112,299],"time.":[113,300],"While":[114],"process":[117],"reduces":[118],"total":[120,171],"number":[121,163,184],"parameters":[123,229],"required":[124],"inference,":[126],"decreases":[128],"precision":[130],"floating":[133],"point.":[134],"We":[135,213,236],"run":[136],"approach":[138],"using":[139,279],"task":[143],"robotic":[146],"arm":[147],"compare":[149,200],"results":[151],"high-end":[154],"constrained":[156,281],"device.":[157],"As":[158],"metrics,":[159],"we":[160,193,199],"consider":[161],"Floating-point":[165],"Operations":[166],"Per":[167],"Second":[168],"(FLOPS),":[169],"mathematical":[173],"computations,":[174],"calculation":[176],"parameters,":[178],"inference":[180],"time,":[181],"video":[186],"frames":[187,294],"processed":[188],"per":[189],"second.":[190],"In":[191],"addition,":[192],"undertake":[194],"qualitative":[196],"evaluation":[197],"where":[198],"output":[202],"predicted":[204],"each":[206],"pruned":[207],"network":[208,218],"with":[209],"original":[211],"one.":[212],"reduced":[214,237],"originally":[216],"proposed":[217,287],"70$$\\%$$":[221,241],"rate,":[223],"implying":[224],"88.86$$\\%$$":[226],"reduction":[227,233],"94.45$$\\%$$":[232],"FLOPS.":[235],"requirement":[239],"by":[240,249],"increasing":[247],"error":[248],"mere":[251],"one":[252],"perceptual":[253],"(P.P).":[255],"metric":[257],"increases":[258],"input":[259],"11.71":[263],"FPS":[264,267,277],"41.9":[266],"Desktop":[270],"case.":[271],"Image":[272],"augmented":[274],"2.86":[276],"device":[282],"10.04":[284],"FPS.":[285],"The":[286],"approach\u2019s":[288],"higher":[289],"rate":[291],"allows":[295],"much":[297],"shorter":[298]},"counts_by_year":[],"updated_date":"2026-01-28T23:14:49.684275","created_date":"2026-01-19T00:00:00"}