{"id":"https://openalex.org/W2317597902","doi":"https://doi.org/10.1109/siu.2015.7129986","title":"SVM for sketch recognition: Which hyperparameter interval to try?","display_name":"SVM for sketch recognition: Which hyperparameter interval to try?","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W2317597902","doi":"https://doi.org/10.1109/siu.2015.7129986","mag":"2317597902"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2015.7129986","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2015.7129986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 23nd Signal Processing and Communications Applications Conference (SIU)","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/A5018139450","display_name":"Kemal Tugrul Yesilbek","orcid":null},"institutions":[{"id":"https://openalex.org/I1351752","display_name":"Ko\u00e7 University","ror":"https://ror.org/00jzwgz36","country_code":"TR","type":"education","lineage":["https://openalex.org/I1351752"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Kemal Tugrul Yesilbek","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Ko\u00e7 \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye"],"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Ko\u00e7 \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I1351752"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032316925","display_name":"Cansu \u015een","orcid":"https://orcid.org/0000-0003-3355-2736"},"institutions":[{"id":"https://openalex.org/I1351752","display_name":"Ko\u00e7 University","ror":"https://ror.org/00jzwgz36","country_code":"TR","type":"education","lineage":["https://openalex.org/I1351752"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Cansu Sen","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Ko\u00e7 \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye"],"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Ko\u00e7 \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I1351752"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103739869","display_name":"Serike Cakmak","orcid":null},"institutions":[{"id":"https://openalex.org/I1351752","display_name":"Ko\u00e7 University","ror":"https://ror.org/00jzwgz36","country_code":"TR","type":"education","lineage":["https://openalex.org/I1351752"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Serike Cakmak","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Ko\u00e7 \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye"],"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Ko\u00e7 \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I1351752"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005565161","display_name":"Tevfik Metin Sezgin","orcid":"https://orcid.org/0000-0002-1524-1646"},"institutions":[{"id":"https://openalex.org/I1351752","display_name":"Ko\u00e7 University","ror":"https://ror.org/00jzwgz36","country_code":"TR","type":"education","lineage":["https://openalex.org/I1351752"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"T. Metin Sezgin","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Ko\u00e7 \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye"],"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc Ko\u00e7 \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I1351752"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5018139450"],"corresponding_institution_ids":["https://openalex.org/I1351752"],"apc_list":null,"apc_paid":null,"fwci":0.4314,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.78322194,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"45","issue":null,"first_page":"943","last_page":"946"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9994000196456909,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9994000196456909,"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/T10057","display_name":"Face and Expression Recognition","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9959999918937683,"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/hyperparameter","display_name":"Hyperparameter","score":0.9677301645278931},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.827285647392273},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.749280571937561},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7067803144454956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.623629629611969},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.622021496295929},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.5088382363319397},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5009951591491699},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43505752086639404},{"id":"https://openalex.org/keywords/sketch-recognition","display_name":"Sketch recognition","score":0.4157399535179138},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.4144856929779053},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4133342504501343},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18203315138816833},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15316084027290344}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.9677301645278931},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.827285647392273},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.749280571937561},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7067803144454956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.623629629611969},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.622021496295929},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.5088382363319397},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5009951591491699},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43505752086639404},{"id":"https://openalex.org/C132900626","wikidata":"https://www.wikidata.org/wiki/Q7534733","display_name":"Sketch recognition","level":4,"score":0.4157399535179138},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.4144856929779053},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4133342504501343},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18203315138816833},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15316084027290344},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu.2015.7129986","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2015.7129986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 23nd Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1645355120","https://openalex.org/W1972420097","https://openalex.org/W2089077920","https://openalex.org/W2108637086","https://openalex.org/W2124557638","https://openalex.org/W2143628522","https://openalex.org/W2152353853","https://openalex.org/W2153635508","https://openalex.org/W2158001550","https://openalex.org/W2907995671"],"related_works":["https://openalex.org/W2953665647","https://openalex.org/W4281646320","https://openalex.org/W4205712847","https://openalex.org/W3169687406","https://openalex.org/W2954882791","https://openalex.org/W4287818966","https://openalex.org/W4388119537","https://openalex.org/W3014750173","https://openalex.org/W3114025147","https://openalex.org/W3192751261"],"abstract_inverted_index":{"Hyperparameters":[0],"are":[1],"among":[2],"the":[3,9,27],"most":[4],"crucial":[5],"factors":[6],"that":[7,68],"effect":[8],"performance":[10,29],"of":[11,32],"machine":[12],"learning":[13],"algorithms.":[14],"Since":[15],"there":[16],"is":[17,45],"not":[18],"a":[19,43,76],"common":[20],"ground":[21],"on":[22,58],"which":[23],"hyperparameter":[24,35,69],"combinations":[25],"give":[26],"highest":[28],"in":[30,80],"terms":[31],"prediction":[33],"accuracy,":[34],"search":[36,70],"needs":[37],"to":[38,46,75],"be":[39,47,73],"conducted":[40],"each":[41],"time":[42],"model":[44],"trained.":[48],"In":[49],"this":[50],"work,":[51],"we":[52],"analyzed":[53],"how":[54],"similar":[55],"hyperparemeters":[56],"perform":[57],"various":[59],"datasets":[60],"from":[61],"sketch":[62],"recognition":[63],"domain.":[64],"Results":[65],"have":[66],"shown":[67],"space":[71],"can":[72],"reduced":[74],"subspace":[77],"despite":[78],"differences":[79],"dataset":[81],"characteristics.":[82]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
