{"id":"https://openalex.org/W2415545456","doi":"https://doi.org/10.1109/icit.2016.7474849","title":"Maximal margin feature mapping via basic image descriptors for image classification","display_name":"Maximal margin feature mapping via basic image descriptors for image classification","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2415545456","doi":"https://doi.org/10.1109/icit.2016.7474849","mag":"2415545456"},"language":"en","primary_location":{"id":"doi:10.1109/icit.2016.7474849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit.2016.7474849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Industrial Technology (ICIT)","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/A5089487881","display_name":"Changchen Zhao","orcid":"https://orcid.org/0000-0002-0546-6016"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]},{"id":"https://openalex.org/I162838928","display_name":"National Chung Hsing University","ror":"https://ror.org/05vn3ca78","country_code":"TW","type":"education","lineage":["https://openalex.org/I162838928"]}],"countries":["CN","TW"],"is_corresponding":true,"raw_author_name":"Changchen Zhao","raw_affiliation_strings":["Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan","School of Automation Science and Electrical Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan","institution_ids":["https://openalex.org/I162838928"]},{"raw_affiliation_string":"School of Automation Science and Electrical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100754708","display_name":"Chun\u2010Liang Lin","orcid":"https://orcid.org/0000-0002-8520-3450"},"institutions":[{"id":"https://openalex.org/I162838928","display_name":"National Chung Hsing University","ror":"https://ror.org/05vn3ca78","country_code":"TW","type":"education","lineage":["https://openalex.org/I162838928"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chun-Liang Lin","raw_affiliation_strings":["Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan","institution_ids":["https://openalex.org/I162838928"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026365889","display_name":"Weihai Chen","orcid":"https://orcid.org/0000-0001-7912-4505"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihai Chen","raw_affiliation_strings":["School of Automation Science and Electrical Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Electrical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5089487881"],"corresponding_institution_ids":["https://openalex.org/I82880672","https://openalex.org/I162838928"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0399674,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":null,"first_page":"775","last_page":"780"},"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":0.9994999766349792,"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":0.9994999766349792,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9925000071525574,"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/T10057","display_name":"Face and Expression Recognition","score":0.9872999787330627,"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/computer-science","display_name":"Computer science","score":0.7383559942245483},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.7168198823928833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7133602499961853},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.6857544183731079},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6662811040878296},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6286202669143677},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5506340265274048},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5392478704452515},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.472282737493515},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.45774123072624207},{"id":"https://openalex.org/keywords/transformation-matrix","display_name":"Transformation matrix","score":0.4530780017375946},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.43849658966064453},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4299236536026001},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2097567617893219}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7383559942245483},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7168198823928833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7133602499961853},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.6857544183731079},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6662811040878296},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6286202669143677},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5506340265274048},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5392478704452515},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.472282737493515},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.45774123072624207},{"id":"https://openalex.org/C165443888","wikidata":"https://www.wikidata.org/wiki/Q1482183","display_name":"Transformation matrix","level":3,"score":0.4530780017375946},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.43849658966064453},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4299236536026001},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2097567617893219},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icit.2016.7474849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit.2016.7474849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Industrial Technology (ICIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1548802052","https://openalex.org/W1551774182","https://openalex.org/W1606858007","https://openalex.org/W1897953826","https://openalex.org/W1900408618","https://openalex.org/W1974647172","https://openalex.org/W2027922120","https://openalex.org/W2029804645","https://openalex.org/W2086402015","https://openalex.org/W2097018403","https://openalex.org/W2097350233","https://openalex.org/W2102605133","https://openalex.org/W2107034620","https://openalex.org/W2110798204","https://openalex.org/W2112274848","https://openalex.org/W2124386111","https://openalex.org/W2136922672","https://openalex.org/W2148809531","https://openalex.org/W2152161678","https://openalex.org/W2153635508","https://openalex.org/W2161969291","https://openalex.org/W2162383208","https://openalex.org/W2162915993","https://openalex.org/W2166049352","https://openalex.org/W3203224907","https://openalex.org/W6633090903","https://openalex.org/W6639854271","https://openalex.org/W6674642818","https://openalex.org/W6676481782","https://openalex.org/W6676759488","https://openalex.org/W6683886257"],"related_works":["https://openalex.org/W3034955165","https://openalex.org/W2094920358","https://openalex.org/W2041448692","https://openalex.org/W2247121321","https://openalex.org/W2391926582","https://openalex.org/W2087391438","https://openalex.org/W1966831329","https://openalex.org/W2316074893","https://openalex.org/W2049930962","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Computer":[0],"vision":[1,21],"is":[2,74,99],"one":[3],"of":[4,120],"the":[5,25,39,47,70,92,103,118,121],"most":[6,26,33],"important":[7,17],"branches":[8],"in":[9,19,29,69],"modern":[10],"industrial":[11],"technology.":[12],"Image":[13],"classification":[14,35],"plays":[15],"an":[16,78],"role":[18],"computer":[20],"since":[22],"it":[23],"utilizes":[24],"advance":[27],"technique":[28],"this":[30],"area.":[31],"However,":[32],"image":[34,51],"methods":[36],"only":[37],"use":[38],"SIFT":[40],"feature":[41,62],"for":[42],"further":[43],"processing,":[44],"which":[45],"hinders":[46],"rich":[48],"useful":[49],"low-level":[50],"attributes":[52],"to":[53,101],"be":[54],"captured.":[55],"This":[56,73],"paper":[57],"proposes":[58],"a":[59],"maximal":[60],"margin":[61],"mapping":[63],"framework":[64],"that":[65,81],"incorporates":[66],"basic":[67],"descriptors":[68],"recognition":[71],"system.":[72],"fulfilled":[75],"by":[76],"optimizing":[77],"objective":[79],"function":[80],"minimizes":[82],"intra-class":[83],"distance":[84,88],"and":[85],"maximizes":[86],"inter-class":[87],"as":[89,91],"well":[90],"reconstruction":[93],"error.":[94],"An":[95],"efficient":[96],"optimization":[97],"algorithm":[98],"proposed":[100,122],"learn":[102],"transformation":[104],"matrix.":[105],"Experiments":[106],"on":[107],"three":[108],"publicly":[109],"available":[110],"datasets":[111],"are":[112],"conducted.":[113],"The":[114],"preliminary":[115],"results":[116],"show":[117],"effectiveness":[119],"approach.":[123]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}