{"id":"https://openalex.org/W3216660574","doi":"https://doi.org/10.1109/icce-tw52618.2021.9603169","title":"Dynamic sample selection method based on classification prediction","display_name":"Dynamic sample selection method based on classification prediction","publication_year":2021,"publication_date":"2021-09-15","ids":{"openalex":"https://openalex.org/W3216660574","doi":"https://doi.org/10.1109/icce-tw52618.2021.9603169","mag":"3216660574"},"language":"en","primary_location":{"id":"doi:10.1109/icce-tw52618.2021.9603169","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-tw52618.2021.9603169","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)","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/A5100742230","display_name":"Xingfu Wang","orcid":"https://orcid.org/0000-0002-1301-3535"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xing-Fu Wang","raw_affiliation_strings":["USTC, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"USTC, Hefei, Anhui, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082590283","display_name":"Pengfei Xie","orcid":"https://orcid.org/0000-0002-3242-6351"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng-Fei Xie","raw_affiliation_strings":["USTC, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"USTC, Hefei, Anhui, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100742230"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15823529,"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":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9987999796867371,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9987999796867371,"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":0.996999979019165,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/pascal","display_name":"Pascal (unit)","score":0.8004810810089111},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7751102447509766},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.635200560092926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6188902258872986},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5741860866546631},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5064080953598022},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4916709065437317},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48995962738990784},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4722273349761963},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.43253734707832336},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42718854546546936},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22954061627388}],"concepts":[{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.8004810810089111},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7751102447509766},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.635200560092926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6188902258872986},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5741860866546631},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5064080953598022},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4916709065437317},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48995962738990784},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4722273349761963},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.43253734707832336},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42718854546546936},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22954061627388},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-tw52618.2021.9603169","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-tw52618.2021.9603169","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2031489346","https://openalex.org/W2565639579","https://openalex.org/W2613718673","https://openalex.org/W2982770724","https://openalex.org/W3035316790","https://openalex.org/W3035396860","https://openalex.org/W3035473155","https://openalex.org/W6620707391","https://openalex.org/W6760947256","https://openalex.org/W6770992763"],"related_works":["https://openalex.org/W3177249605","https://openalex.org/W4376620596","https://openalex.org/W2534152068","https://openalex.org/W4299545679","https://openalex.org/W1972515067","https://openalex.org/W1689909837","https://openalex.org/W4293054914","https://openalex.org/W2549121492","https://openalex.org/W3138508047","https://openalex.org/W4313315626"],"abstract_inverted_index":{"Recent":[0],"research":[1],"has":[2],"shown":[3],"that":[4,41],"sample":[5,43,61],"selection":[6,44,62],"in":[7,74,97],"the":[8,15,98],"training":[9,48],"phase":[10],"is":[11,45],"crucial":[12],"for":[13,47],"improving":[14],"accuracy":[16],"of":[17],"object":[18,50],"detection.":[19],"For":[20],"a":[21,57],"long":[22],"time,":[23],"we":[24,55],"always":[25],"use":[26],"manually":[27],"designed":[28],"IoU":[29,67],"threshold":[30],"to":[31],"filter":[32],"out":[33],"low-quality":[34],"candidates,":[35],"but":[36],"recently":[37],"some":[38],"work":[39],"shows":[40],"dynamic":[42,60],"better":[46],"an":[49],"detector.":[51],"In":[52],"our":[53,85],"paper,":[54],"present":[56],"new":[58],"adaptive":[59],"strategy":[63],"based":[64],"on":[65],"both":[66],"and":[68],"Classification":[69],"prediction.":[70],"Our":[71],"experiment":[72],"applies":[73],"PASCAL":[75],"VOC":[76],"dataset,":[77],"without":[78],"any":[79,89],"whistle,":[80],"achieved":[81],"84%":[82],"mAP.":[83],"Also,":[84],"method":[86],"doesn\u2019t":[87],"require":[88],"extra":[90],"computation,":[91],"which":[92],"can":[93],"guarantee":[94],"high":[95],"speed":[96],"testing":[99],"phase.":[100]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
