{"id":"https://openalex.org/W2528355985","doi":"https://doi.org/10.1109/iccse.2016.7581686","title":"Learning to detect salient curves of cartoon images based on composition rules","display_name":"Learning to detect salient curves of cartoon images based on composition rules","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2528355985","doi":"https://doi.org/10.1109/iccse.2016.7581686","mag":"2528355985"},"language":"en","primary_location":{"id":"doi:10.1109/iccse.2016.7581686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccse.2016.7581686","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 11th International Conference on Computer Science & Education (ICCSE)","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/A5100418473","display_name":"Chen Chen","orcid":"https://orcid.org/0000-0002-5817-5693"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Chen","raw_affiliation_strings":["Software School, Xiamen University, Xiamen, Fujian, P.R. China"],"affiliations":[{"raw_affiliation_string":"Software School, Xiamen University, Xiamen, Fujian, P.R. China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056910392","display_name":"Juncong Lin","orcid":"https://orcid.org/0000-0001-6500-6655"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juncong Lin","raw_affiliation_strings":["Software School, Xiamen University, Xiamen, Fujian, P.R. China"],"affiliations":[{"raw_affiliation_string":"Software School, Xiamen University, Xiamen, Fujian, P.R. China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074344681","display_name":"Minghong Liao","orcid":"https://orcid.org/0000-0002-0197-7273"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghong Liao","raw_affiliation_strings":["Software School, Xiamen University, Xiamen, Fujian, P.R. China"],"affiliations":[{"raw_affiliation_string":"Software School, Xiamen University, Xiamen, Fujian, P.R. China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100601430","display_name":"Guilin Li","orcid":"https://orcid.org/0000-0001-7301-5391"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guilin Li","raw_affiliation_strings":["Software School, Xiamen University, Xiamen, Fujian, P.R. China"],"affiliations":[{"raw_affiliation_string":"Software School, Xiamen University, Xiamen, Fujian, P.R. China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069179331","display_name":"Guohua Huang","orcid":"https://orcid.org/0000-0001-7780-7409"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guohua Huang","raw_affiliation_strings":["Software School, Xiamen University, Xiamen, Fujian, P.R. China"],"affiliations":[{"raw_affiliation_string":"Software School, Xiamen University, Xiamen, Fujian, P.R. China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100418473"],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":0.1695,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58092137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"808","last_page":"813"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":1.0,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":1.0,"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/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9764999747276306,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9753000140190125,"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/salient","display_name":"Salient","score":0.8842251300811768},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.688966691493988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6068468689918518},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5482344031333923},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4789752960205078},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4532252252101898},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43420732021331787},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41797035932540894},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.41451483964920044},{"id":"https://openalex.org/keywords/diagonal","display_name":"Diagonal","score":0.412570595741272},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4116401672363281},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2889469265937805}],"concepts":[{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.8842251300811768},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.688966691493988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6068468689918518},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5482344031333923},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4789752960205078},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4532252252101898},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43420732021331787},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41797035932540894},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.41451483964920044},{"id":"https://openalex.org/C130367717","wikidata":"https://www.wikidata.org/wiki/Q189791","display_name":"Diagonal","level":2,"score":0.412570595741272},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4116401672363281},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2889469265937805},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccse.2016.7581686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccse.2016.7581686","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 11th International Conference on Computer Science & Education (ICCSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1872412942","https://openalex.org/W1965301399","https://openalex.org/W1982793155","https://openalex.org/W1988195734","https://openalex.org/W1996326832","https://openalex.org/W2037954058","https://openalex.org/W2041719651","https://openalex.org/W2078132377","https://openalex.org/W2100470808","https://openalex.org/W2128272608","https://openalex.org/W2135957164","https://openalex.org/W2146103513","https://openalex.org/W2148143831","https://openalex.org/W4239147634"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W28991112","https://openalex.org/W2370726991","https://openalex.org/W2135584473","https://openalex.org/W2369710579","https://openalex.org/W4327728159","https://openalex.org/W4394266730","https://openalex.org/W1990856605","https://openalex.org/W2053783616","https://openalex.org/W2545348020"],"abstract_inverted_index":{"As":[0],"a":[1,45,66,149],"basic":[2],"operation,":[3],"image":[4],"saliency":[5],"detection":[6,42,102],"has":[7,148],"been":[8,17],"widely":[9],"used":[10],"in":[11,118],"various":[12],"applications.":[13],"Many":[14],"approaches":[15],"have":[16],"proposed":[18],"to":[19,28,72,132,139],"detect":[20,29,140],"salient":[21,30,52,100,141],"regions.":[22],"In":[23],"this":[24],"study,":[25],"we":[26,50],"learn":[27],"curves":[31,53,81,142],"of":[32,68,92],"cartoon":[33,62],"images":[34,119],"based":[35],"on":[36,99],"composition":[37,73,123],"rules.":[38,124],"We":[39,64,95,125],"formulate":[40],"the":[41,55,61,77,83,85,87,90,93,104,128],"problem":[43],"as":[44,76],"binary":[46],"labeling":[47],"task":[48],"where":[49],"separate":[51],"from":[54,60],"whole":[56],"curve":[57,69,101],"structures":[58],"extracted":[59],"image.":[63,94],"choose":[65],"set":[67],"features":[70,113],"related":[71],"rules,":[74],"such":[75],"positional":[78],"relationship":[79],"between":[80],"and":[82,109,135,146],"center,":[84],"diagonals,":[86],"symmetries":[88],"or":[89],"thirds":[91],"evaluate":[96],"their":[97],"effects":[98],"by":[103],"information":[105],"gain":[106],"ranking":[107],"filter":[108],"find":[110],"that":[111],"these":[112,137],"play":[114],"an":[115],"important":[116],"role":[117],"respectively":[120],"with":[121],"different":[122],"also":[126],"use":[127,136],"random":[129],"forest":[130],"classifier":[131],"build":[133],"models":[134,138],"for":[143],"new":[144],"images,":[145],"it":[147],"satisfactory":[150],"result.":[151]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}