{"id":"https://openalex.org/W7223658898","doi":"https://doi.org/10.1109/idap71869.2026.11728227","title":"Pinhole Tabanl\u0131 Sentetik Veriyle E\u011fitilmi\u015f MLP ile \u00d6zel Tasar\u0131m Etiket Tabanl\u0131 Poz ve Mesafe Tahmini","display_name":"Pinhole Tabanl\u0131 Sentetik Veriyle E\u011fitilmi\u015f MLP ile \u00d6zel Tasar\u0131m Etiket Tabanl\u0131 Poz ve Mesafe Tahmini","publication_year":2026,"publication_date":"2026-09-01","ids":{"openalex":"https://openalex.org/W7223658898","doi":"https://doi.org/10.1109/idap71869.2026.11728227"},"language":"tr","primary_location":{"id":"doi:10.1109/idap71869.2026.11728227","doi":"https://doi.org/10.1109/idap71869.2026.11728227","is_oa":true,"landing_page_url":"https://doi.org/10.1109/idap71869.2026.11728227","pdf_url":null,"source":{"id":"https://openalex.org/S4306498172","display_name":"International Artificial Intelligence and Data Processing Symposium (IDAP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 10th International Artificial Intelligence and Data Processing Symposium (IDAP)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/idap71869.2026.11728227","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048858194","display_name":"Emre Erkan","orcid":"https://orcid.org/0000-0003-0187-4079","observed_orcids":["https://orcid.org/0000-0003-0187-4079"]},"institutions":[{"id":"https://openalex.org/I32481161","display_name":"Batman University","ror":"https://ror.org/051tsqh55","country_code":"TR","type":"education","lineage":["https://openalex.org/I32481161"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Emre Erkan","raw_affiliation_strings":["Teknik Bilimler Meslek Y\u00fcksekokulu, Batman \u00dcniversitesi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Teknik Bilimler Meslek Y\u00fcksekokulu, Batman \u00dcniversitesi","institution_ids":["https://openalex.org/I32481161"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5048858194"],"corresponding_institution_ids":["https://openalex.org/I32481161"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.79852476,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.35420000553131104,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.35420000553131104,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.14970000088214874,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.0674000009894371,"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/pose-estimation","display_name":"pose estimation","score":0.6890000104904175},{"id":"https://openalex.org/keywords/distance-estimation","display_name":"distance estimation","score":0.9559999704360962},{"id":"https://openalex.org/keywords/pinhole-camera","display_name":"pinhole camera","score":0.7369999885559082},{"id":"https://openalex.org/keywords/geometric-feature-extraction","display_name":"geometric feature extraction","score":0.9490000009536743},{"id":"https://openalex.org/keywords/visual-localization","display_name":"visual localization","score":0.6669999957084656},{"id":"https://openalex.org/keywords/object-localization","display_name":"object localization","score":0.31200000643730164},{"id":"https://openalex.org/keywords/robotic-manipulation","display_name":"robotic manipulation","score":0.5130000114440918},{"id":"https://openalex.org/keywords/augmented-reality","display_name":"augmented reality","score":0.8930000066757202},{"id":"https://openalex.org/keywords/human-machine-interaction","display_name":"human-machine interaction","score":0.8220000267028809},{"id":"https://openalex.org/keywords/reprojection","display_name":"reprojection","score":0.4749999940395355}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5170999765396118},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4099000096321106},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33739998936653137},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3025999963283539},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2994000017642975},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.29440000653266907},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.23720000684261322},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.23080000281333923},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.22429999709129333}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/idap71869.2026.11728227","doi":"https://doi.org/10.1109/idap71869.2026.11728227","is_oa":true,"landing_page_url":"https://doi.org/10.1109/idap71869.2026.11728227","pdf_url":null,"source":{"id":"https://openalex.org/S4306498172","display_name":"International Artificial Intelligence and Data Processing Symposium (IDAP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 10th International Artificial Intelligence and Data Processing Symposium (IDAP)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/idap71869.2026.11728227","doi":"https://doi.org/10.1109/idap71869.2026.11728227","is_oa":true,"landing_page_url":"https://doi.org/10.1109/idap71869.2026.11728227","pdf_url":null,"source":{"id":"https://openalex.org/S4306498172","display_name":"International Artificial Intelligence and Data Processing Symposium (IDAP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 10th International Artificial Intelligence and Data Processing Symposium (IDAP)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2741269719","https://openalex.org/W2263967768","https://openalex.org/W2611917656","https://openalex.org/W4415297317","https://openalex.org/W7160311610","https://openalex.org/W3090184543","https://openalex.org/W72047071","https://openalex.org/W7196982792","https://openalex.org/W3107918608","https://openalex.org/W7029141459"],"abstract_inverted_index":{"This":[0],"study":[1,20],"focuses":[2],"on":[3,146],"estimating":[4],"the":[5,35,56,68,72,78,82,100,115,121,154,187],"pose":[6],"and":[7,45,75,88,138,144,172,195],"distance":[8],"information":[9],"of":[10,71,81,109,189],"objects":[11],"using":[12,29,50],"a":[13,22],"custom-designed":[14],"tag.":[15],"In":[16,34],"this":[17,19],"context,":[18],"presents":[21],"multi-output":[23,122],"Multilayer":[24],"Perceptron":[25],"(MLP)":[26],"model":[27,86,116],"trained":[28],"pinhole-based":[30,139],"synthetic":[31,38,102],"measurement":[32,39],"data.":[33],"proposed":[36],"method,":[37],"data":[40,80],"covering":[41],"different":[42],"distance,":[43],"image-center,":[44],"orientation":[46],"conditions":[47],"were":[48,91],"generated":[49],"effective":[51],"pinhole":[52],"parameters":[53],"consistent":[54,118],"with":[55,186],"real":[57],"camera":[58],"geometry.":[59],"A":[60],"19-dimensional":[61],"geometric":[62,133],"feature":[63,134],"set":[64],"was":[65,111],"extracted":[66],"from":[67],"center":[69],"positions":[70],"tag":[73],"sub-components":[74],"used":[76],"as":[77,167],"input":[79],"MLP":[83],"model.":[84],"The":[85,149],"architecture":[87],"training":[89],"hyperparameters":[90],"systematically":[92],"determined":[93],"through":[94],"an":[95,105,157],"Optuna-based":[96],"search":[97],"process.":[98],"On":[99],"independent":[101],"test":[103],"set,":[104],"overall":[106],"R2":[107],"value":[108],"0.9873":[110],"obtained,":[112],"suggesting":[113],"that":[114,128,153],"exhibited":[117],"performance":[119],"in":[120,164,193],"estimation":[123],"task.":[124],"Real-environment":[125],"tests":[126],"showed":[127],"ROI":[129],"determination,":[130],"subcomponent":[131],"detection,":[132],"extraction,":[135],"MLP-based":[136],"estimation,":[137],"reprojection":[140],"could":[141],"be":[142,184],"integrated":[143],"executed":[145],"video":[147],"frames.":[148],"obtained":[150],"results":[151],"show":[152],"method":[155],"provides":[156],"applicable":[158],"framework":[159],"for":[160],"visual":[161],"localization":[162],"tasks":[163],"areas":[165],"such":[166],"robotic":[168],"manipulation,":[169],"augmented":[170],"reality,":[171],"human-machine":[173],"interaction.":[174],"As":[175],"future":[176],"work,":[177],"alternative":[178],"regression":[179],"strategies":[180],"are":[181],"planned":[182],"to":[183],"investigated":[185],"aim":[188],"reducing":[190],"deviations,":[191],"particularly":[192],"yaw":[194],"pitch":[196],"estimation.":[197]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-10-27T00:00:00"}