{"id":"https://openalex.org/W2103877845","doi":"https://doi.org/10.1109/coginf.2010.5599745","title":"Mining for high complexity regions using entropy and box counting dimension quad-trees","display_name":"Mining for high complexity regions using entropy and box counting dimension quad-trees","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W2103877845","doi":"https://doi.org/10.1109/coginf.2010.5599745","mag":"2103877845"},"language":"en","primary_location":{"id":"doi:10.1109/coginf.2010.5599745","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginf.2010.5599745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","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/A5081035280","display_name":"Rosanne Vetro","orcid":null},"institutions":[{"id":"https://openalex.org/I33434090","display_name":"University of Massachusetts Boston","ror":"https://ror.org/04ydmy275","country_code":"US","type":"education","lineage":["https://openalex.org/I33434090"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rosanne Vetro","raw_affiliation_strings":["Department of Computer Science, University of Massachusetts, Boston, Boston, MA, USA","Univ. of Massachusetts Boston, Dept. of Comp. Science, 100 Morrissey Blvd., Boston, Massachusetts 02125 USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Massachusetts, Boston, Boston, MA, USA","institution_ids":["https://openalex.org/I33434090"]},{"raw_affiliation_string":"Univ. of Massachusetts Boston, Dept. of Comp. Science, 100 Morrissey Blvd., Boston, Massachusetts 02125 USA","institution_ids":["https://openalex.org/I33434090"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088432110","display_name":"Wei Ding","orcid":"https://orcid.org/0000-0002-3383-551X"},"institutions":[{"id":"https://openalex.org/I33434090","display_name":"University of Massachusetts Boston","ror":"https://ror.org/04ydmy275","country_code":"US","type":"education","lineage":["https://openalex.org/I33434090"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Ding","raw_affiliation_strings":["Department of Computer Science, University of Massachusetts, Boston, Boston, MA, USA","Univ. of Massachusetts Boston, Dept. of Comp. Science, 100 Morrissey Blvd., Boston, Massachusetts 02125 USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Massachusetts, Boston, Boston, MA, USA","institution_ids":["https://openalex.org/I33434090"]},{"raw_affiliation_string":"Univ. of Massachusetts Boston, Dept. of Comp. Science, 100 Morrissey Blvd., Boston, Massachusetts 02125 USA","institution_ids":["https://openalex.org/I33434090"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072140970","display_name":"Dan A. Simovici","orcid":null},"institutions":[{"id":"https://openalex.org/I33434090","display_name":"University of Massachusetts Boston","ror":"https://ror.org/04ydmy275","country_code":"US","type":"education","lineage":["https://openalex.org/I33434090"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan A. Simovici","raw_affiliation_strings":["Department of Computer Science, University of Massachusetts, Boston, Boston, MA, USA","Univ. of Massachusetts Boston, Dept. of Comp. Science, 100 Morrissey Blvd., Boston, Massachusetts 02125 USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Massachusetts, Boston, Boston, MA, USA","institution_ids":["https://openalex.org/I33434090"]},{"raw_affiliation_string":"Univ. of Massachusetts Boston, Dept. of Comp. Science, 100 Morrissey Blvd., Boston, Massachusetts 02125 USA","institution_ids":["https://openalex.org/I33434090"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081035280"],"corresponding_institution_ids":["https://openalex.org/I33434090"],"apc_list":null,"apc_paid":null,"fwci":0.4655,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74711583,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"5284","issue":null,"first_page":"168","last_page":"173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9882000088691711,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9882000088691711,"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/T11017","display_name":"Chaos-based Image/Signal Encryption","score":0.9861000180244446,"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/T12002","display_name":"Computability, Logic, AI Algorithms","score":0.9855999946594238,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/box-counting","display_name":"Box counting","score":0.7008432149887085},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6392611265182495},{"id":"https://openalex.org/keywords/fractal-dimension","display_name":"Fractal dimension","score":0.6303732395172119},{"id":"https://openalex.org/keywords/fractal","display_name":"Fractal","score":0.5549307465553284},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5329276919364929},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5308645367622375},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5163170695304871},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5108806490898132},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5033397078514099},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.48876357078552246},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.399235337972641},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39330539107322693},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3831579387187958},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37470266222953796},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.355260968208313},{"id":"https://openalex.org/keywords/fractal-analysis","display_name":"Fractal analysis","score":0.24513232707977295},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.17306369543075562}],"concepts":[{"id":"https://openalex.org/C99008458","wikidata":"https://www.wikidata.org/wiki/Q4951583","display_name":"Box counting","level":5,"score":0.7008432149887085},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6392611265182495},{"id":"https://openalex.org/C26546657","wikidata":"https://www.wikidata.org/wiki/Q1412452","display_name":"Fractal dimension","level":3,"score":0.6303732395172119},{"id":"https://openalex.org/C40636538","wikidata":"https://www.wikidata.org/wiki/Q81392","display_name":"Fractal","level":2,"score":0.5549307465553284},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5329276919364929},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5308645367622375},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5163170695304871},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5108806490898132},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5033397078514099},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.48876357078552246},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.399235337972641},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39330539107322693},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3831579387187958},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37470266222953796},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.355260968208313},{"id":"https://openalex.org/C162494671","wikidata":"https://www.wikidata.org/wiki/Q2845227","display_name":"Fractal analysis","level":4,"score":0.24513232707977295},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.17306369543075562},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/coginf.2010.5599745","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginf.2010.5599745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.185.3629","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.185.3629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.umb.edu/%7Eding/papers/icci2010_vetro.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1543075725","https://openalex.org/W1557577278","https://openalex.org/W1606626938","https://openalex.org/W4234438057","https://openalex.org/W6633601057"],"related_works":["https://openalex.org/W2394117909","https://openalex.org/W2896054214","https://openalex.org/W2355197944","https://openalex.org/W2017118246","https://openalex.org/W2360338089","https://openalex.org/W2354661593","https://openalex.org/W2382240109","https://openalex.org/W3095001701","https://openalex.org/W4312128086","https://openalex.org/W4312776762"],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"an":[3,45],"algorithm":[4],"for":[5,37,145],"capturing":[6],"high":[7,87,128],"complexity":[8],"regions":[9],"of":[10,61,72,108,124,160],"a":[11,73,113,166],"data":[12],"domain.":[13],"In":[14,27],"this":[15],"work,":[16],"we":[17,29,164],"focus":[18],"on":[19,49,94,136,142],"domains":[20],"in":[21,127],"R":[22],"<sup":[23],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[24],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[25],".":[26],"particular,":[28],"analyze":[30],"2-dimensional":[31],"image":[32],"domains.":[33],"Two":[34],"different":[35],"methods":[36,170],"mining":[38],"are":[39,82,103],"considered.":[40],"The":[41,55,116],"first":[42],"method":[43,57],"performs":[44],"information-theoretic":[46],"analysis":[47],"based":[48],"entropy":[50],"to":[51,65,100],"find":[52],"diverse":[53],"areas.":[54],"second":[56],"applies":[58],"the":[59,70,91,95,106,109,119,122,133,137,152,155,161,169],"concept":[60],"box-counting":[62],"dimension":[63],"related":[64],"fractal":[66],"geometry.":[67],"We":[68],"propose":[69],"use":[71],"quad-tree":[74,139],"as":[75],"main":[76],"search":[77],"structure":[78],"where":[79],"complex":[80],"areas":[81],"represented":[83],"by":[84],"leaves":[85],"with":[86],"feature":[88,111,130],"values":[89],"at":[90,132],"highest":[92,134],"level":[93,107,135],"tree.":[96],"Nodes":[97],"that":[98],"refer":[99],"specific":[101],"sub-domains":[102,131],"split":[104],"when":[105],"analyzed":[110],"exceeds":[112],"chosen":[114],"threshold.":[115],"relationship":[117],"between":[118,154,168],"threshold":[120],"and":[121,158],"number":[123],"pixels":[125],"located":[126],"value":[129],"resultant":[138],"is":[140],"demonstrated":[141],"test":[143],"images":[144],"both":[146],"methods.":[147],"Experimental":[148],"results":[149],"also":[150],"show":[151],"relation":[153],"former":[156],"measurements":[157],"characteristics":[159],"images.":[162],"Finally,":[163],"identify":[165],"correlation":[167],"presented.":[171]},"counts_by_year":[{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
