{"id":"https://openalex.org/W2902064270","doi":"https://doi.org/10.1109/icpr.2018.8545100","title":"Rotational Invariant Discriminant Subspace Learning For Image Classification","display_name":"Rotational Invariant Discriminant Subspace Learning For Image Classification","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902064270","doi":"https://doi.org/10.1109/icpr.2018.8545100","mag":"2902064270"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545100","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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/A5039671101","display_name":"Qiaolin Ye","orcid":"https://orcid.org/0000-0002-8793-8610"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiaolin Ye","raw_affiliation_strings":["College of Information Science and Technology, Nanjing Forestry University, Nanjing, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Nanjing Forestry University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100423029","display_name":"Zhao Zhang","orcid":"https://orcid.org/0000-0002-5703-7969"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5039671101"],"corresponding_institution_ids":["https://openalex.org/I167027274"],"apc_list":null,"apc_paid":null,"fwci":0.2089,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56767419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"34","issue":null,"first_page":"1217","last_page":"1222"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9976999759674072,"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/T10057","display_name":"Face and Expression Recognition","score":0.9976999759674072,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.9873999953269958,"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/discriminant","display_name":"Discriminant","score":0.711897075176239},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7032641172409058},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6708285808563232},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6208151578903198},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6149155497550964},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.6145464777946472},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5322335362434387},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5007147789001465},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4847959578037262},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4729682505130768},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4707130789756775},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46670010685920715},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.44451698660850525},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.2998572885990143},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28819334506988525}],"concepts":[{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.711897075176239},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7032641172409058},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6708285808563232},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6208151578903198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6149155497550964},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.6145464777946472},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5322335362434387},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5007147789001465},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4847959578037262},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4729682505130768},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4707130789756775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46670010685920715},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.44451698660850525},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2998572885990143},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28819334506988525},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8545100","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W147992333","https://openalex.org/W211921589","https://openalex.org/W1166921479","https://openalex.org/W1967086152","https://openalex.org/W1968266099","https://openalex.org/W1989267105","https://openalex.org/W1992633833","https://openalex.org/W2008277111","https://openalex.org/W2028312814","https://openalex.org/W2036295561","https://openalex.org/W2042453128","https://openalex.org/W2053090063","https://openalex.org/W2083955318","https://openalex.org/W2098004870","https://openalex.org/W2102544846","https://openalex.org/W2109531142","https://openalex.org/W2131777119","https://openalex.org/W2134262590","https://openalex.org/W2135081536","https://openalex.org/W2138451337","https://openalex.org/W2151416140","https://openalex.org/W2153963799","https://openalex.org/W2157032359","https://openalex.org/W2163376981","https://openalex.org/W2183198701","https://openalex.org/W2240559667","https://openalex.org/W2253898352","https://openalex.org/W2257217404","https://openalex.org/W2428936319","https://openalex.org/W2464913182","https://openalex.org/W2516176725","https://openalex.org/W2543969232","https://openalex.org/W2548608220","https://openalex.org/W2604160250","https://openalex.org/W2699934687","https://openalex.org/W3014771378","https://openalex.org/W6661018422","https://openalex.org/W6676189307","https://openalex.org/W6679749283","https://openalex.org/W6685928903","https://openalex.org/W6736485867","https://openalex.org/W6740128106"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W3008559849","https://openalex.org/W2371177901"],"abstract_inverted_index":{"A":[0],"novel":[1],"discriminant":[2],"analysis":[3,64],"technique":[4],"for":[5],"feature":[6],"extraction,":[7],"referred":[8],"to":[9,51],"as":[10],"Robust":[11],"Discriminant":[12],"Subspace":[13],"(RDS)":[14],"with":[15],"L2,p+s-Norm":[16],"Distance":[17],"Maximization-Minimization":[18],"(maxmin)":[19],"is":[20,40,49,57],"posed.":[21],"In":[22],"its":[23],"objective,":[24,55],"the":[25,53,66,69],"within-class":[26],"and":[27,34,42,74],"between-class":[28],"distances":[29],"are":[30,79],"measured":[31],"by":[32,82],"L2,p-norm":[33],"L2,s-norm,":[35],"respectively,":[36],"such":[37],"that":[38],"it":[39],"robust":[41],"rotational":[43],"invariant.":[44],"An":[45],"efficient":[46],"iterative":[47],"algorithm":[48],"designed":[50],"solve":[52],"resulted":[54],"which":[56],"non-greedy.":[58],"We":[59],"also":[60],"conduct":[61],"some":[62],"insightful":[63],"on":[65,86],"convergence":[67],"of":[68,76],"proposed":[70],"algorithm.":[71],"Theoretical":[72],"insights":[73],"effectiveness":[75],"our":[77],"RDS":[78],"further":[80],"supported":[81],"promising":[83],"experimental":[84],"results":[85],"several":[87],"images":[88],"databases.":[89]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}