{"id":"https://openalex.org/W2408843399","doi":"https://doi.org/10.1109/acpr.2015.7486450","title":"IAPR keynote lecture III: Methods of achieving perfect recognition scores","display_name":"IAPR keynote lecture III: Methods of achieving perfect recognition scores","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2408843399","doi":"https://doi.org/10.1109/acpr.2015.7486450","mag":"2408843399"},"language":"en","primary_location":{"id":"doi:10.1109/acpr.2015.7486450","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2015.7486450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","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/A5059479627","display_name":"Ching Y. Suen","orcid":"https://orcid.org/0000-0003-1209-7631"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Ching Yee Suen","raw_affiliation_strings":["Concordia University, Canada"],"affiliations":[{"raw_affiliation_string":"Concordia University, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5059479627"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1581969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"xix","last_page":"xix"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.7875999808311462,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.7875999808311462,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.6869000196456909,"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/T12676","display_name":"Machine Learning and ELM","score":0.6791999936103821,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/skeletonization","display_name":"Skeletonization","score":0.7501645088195801},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7216023802757263},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6336033344268799},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5642611980438232},{"id":"https://openalex.org/keywords/heading","display_name":"Heading (navigation)","score":0.5601081252098083},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4879090487957001},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4237288236618042},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12332382798194885},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11325299739837646}],"concepts":[{"id":"https://openalex.org/C23951316","wikidata":"https://www.wikidata.org/wiki/Q1984140","display_name":"Skeletonization","level":2,"score":0.7501645088195801},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7216023802757263},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6336033344268799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5642611980438232},{"id":"https://openalex.org/C2776937971","wikidata":"https://www.wikidata.org/wiki/Q4384217","display_name":"Heading (navigation)","level":2,"score":0.5601081252098083},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4879090487957001},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4237288236618042},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12332382798194885},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11325299739837646},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acpr.2015.7486450","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2015.7486450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2132416234","https://openalex.org/W2118553688","https://openalex.org/W2092783742","https://openalex.org/W2292955152","https://openalex.org/W2376130299","https://openalex.org/W4220907282","https://openalex.org/W1603323139","https://openalex.org/W41790368","https://openalex.org/W2623093699","https://openalex.org/W2381976855"],"abstract_inverted_index":{"Recognition":[0],"systems":[1],"inevitably":[2],"make":[3],"some":[4,8],"errors":[5,15],"somewhere":[6],"at":[7],"time.":[9],"Achieving":[10],"perfect":[11,109],"recognition":[12,75],"without":[13],"making":[14],"has":[16],"been":[17],"the":[18,23,74],"dream":[19],"of":[20,25,41,53,85,92,106],"researchers":[21],"in":[22,49],"field":[24],"pattern":[26],"recognition.":[27],"This":[28],"talk":[29,43],"summarizes":[30],"my":[31,46],"efforts":[32,48],"and":[33,59,69,87,90,101,117],"experiences":[34],"towards":[35,108],"this":[36,42],"goal.":[37],"The":[38],"first":[39],"part":[40],"will":[44,111],"describe":[45],"early":[47],"building":[50],"different":[51],"types":[52,84],"classifiers":[54,79],"based":[55],"on":[56],"structural":[57,88],"analyses":[58],"skeletonization,":[60],"density":[61],"distributions,":[62],"neural":[63],"networks,":[64],"tree":[65],"hierarchies,":[66],"support":[67],"vectors,":[68],"so":[70],"on.":[71],"To":[72],"improve":[73],"rates":[76],"further,":[77],"multiple":[78],"were":[80,99],"explored":[81],"involving":[82],"numerous":[83],"geometric":[86],"features,":[89],"ensembles":[91],"hybrid":[93],"classifiers.":[94],"Later,":[95],"error":[96],"reduction":[97],"machines":[98],"introduced":[100],"investigated.":[102],"Several":[103],"effective":[104],"ways":[105],"heading":[107],"scores":[110],"be":[112],"presented":[113],"with":[114],"real-life":[115],"examples":[116],"promising":[118],"research":[119],"results.":[120]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
