{"id":"https://openalex.org/W6963644868","doi":"https://doi.org/10.21227/af5p-mp40","title":"Simulated and phantom colon data for 6-dof camera pose estimation","display_name":"Simulated and phantom colon data for 6-dof camera pose estimation","publication_year":2022,"publication_date":"2022-12-07","ids":{"openalex":"https://openalex.org/W6963644868","doi":"https://doi.org/10.21227/af5p-mp40"},"language":"en","primary_location":{"id":"doi:10.21227/af5p-mp40","is_oa":true,"landing_page_url":"https://doi.org/10.21227/af5p-mp40","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.21227/af5p-mp40","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Tan, Min","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tan, Min","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/imaging-phantom","display_name":"Imaging phantom","score":0.6877999901771545},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.5738000273704529},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4740999937057495},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.44749999046325684},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.43639999628067017},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42820000648498535},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.40290001034736633}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7476999759674072},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7139000296592712},{"id":"https://openalex.org/C104293457","wikidata":"https://www.wikidata.org/wiki/Q28324852","display_name":"Imaging phantom","level":2,"score":0.6877999901771545},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6319000124931335},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.5738000273704529},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4740999937057495},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.43639999628067017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42820000648498535},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.40290001034736633},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.39730000495910645},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.3840999901294708},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.35670000314712524},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.3440000116825104},{"id":"https://openalex.org/C154020017","wikidata":"https://www.wikidata.org/wiki/Q520171","display_name":"Repeatability","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.3176000118255615},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.30379998683929443},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21227/af5p-mp40","is_oa":true,"landing_page_url":"https://doi.org/10.21227/af5p-mp40","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"dataset"}],"best_oa_location":{"id":"doi:10.21227/af5p-mp40","is_oa":true,"landing_page_url":"https://doi.org/10.21227/af5p-mp40","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Since":[0],"narrow":[1],"imaging":[2],"and":[3,20,53,78,87,107,134,150],"texture":[4],"scarceness":[5],"issues":[6],"results":[7],"to":[8,25,92,114,136],"high":[9],"missing":[10],"rate":[11],"&nbsp;for":[12],"gastrointestinal":[13],"disease":[14],"in":[15,76],"clinical":[16],"colonoscopy,":[17],"the":[18,27,47,58,94,116,138,154],"pose":[19,74],"depth":[21],"estimation":[22,75],"is":[23,90],"required":[24],"improve":[26],"quality":[28],"of":[29,57,96,109,118,140,157],"diagnosis.&nbsp;":[30],"&nbsp;":[31,133],"Some":[32],"unsupervised":[33],"methods":[34,43],"have":[35],"been":[36],"proposed":[37,91,147],"for":[38,50,73,99,105],"this":[39,62],"purpose.":[40],"However,":[41],"these":[42],"often":[44],"suffer":[45],"from":[46],"performance":[48,156],"degradation":[49],"a":[51,83,125],"long":[52,77],"curved":[54,79],"trajectory":[55],"because":[56],"structural":[59],"constraints.":[60],"In":[61,121],"paper,":[63],"we":[64,123],"propose":[65,124],"an":[66],"innovative":[67],"key":[68,100,110],"points":[69,111],"encoding":[70],"Transformer":[71],"(KPEformer)":[72],"colonoscopy":[80],"trajectory.":[81],"Specifically,":[82],"light":[84],"weight":[85],"convolution":[86],"attention":[88],"module":[89],"encode":[93],"features":[95],"latent":[97],"variables":[98],"points.":[101],"Two":[102],"loss":[103],"functions":[104],"confidence":[106],"repeatability":[108],"are":[112],"designed":[113],"enhance":[115],"reliabilty":[117],"output":[119],"information.":[120],"addition,":[122],"more":[126],"adequate":[127],"colon":[128],"dataset":[129,149,152],"which":[130],"contains":[131],"synthetic&nbsp;":[132],"phantom":[135,151],"remedy":[137],"deficiency":[139],"existing":[141],"dataset.":[142],"Extensive":[143],"experiments":[144],"on":[145],"our":[146,158],"synthetic":[148],"demonstrate":[153],"state-of-the-art":[155],"method.":[159]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}
