{"id":"https://openalex.org/W2127628554","doi":"https://doi.org/10.1109/avss.2009.84","title":"A Multi-scale Piecewise-Linear Feature Detector for Spectrogram Tracks","display_name":"A Multi-scale Piecewise-Linear Feature Detector for Spectrogram Tracks","publication_year":2009,"publication_date":"2009-09-01","ids":{"openalex":"https://openalex.org/W2127628554","doi":"https://doi.org/10.1109/avss.2009.84","mag":"2127628554"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2009.84","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://eprints.whiterose.ac.uk/67984/1/Lampert09Multi_ScalePiecewise_LinearFeatureDetector.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016714459","display_name":"Thomas Lampert","orcid":"https://orcid.org/0000-0002-4911-3941"},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Thomas A. Lampert","raw_affiliation_strings":["[Dept. of Comput. Sci., Univ. of York, York, UK]"],"affiliations":[{"raw_affiliation_string":"[Dept. of Comput. Sci., Univ. of York, York, UK]","institution_ids":["https://openalex.org/I52099693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058636317","display_name":"Nick Pears","orcid":null},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nick E. Pears","raw_affiliation_strings":["[Dept. of Comput. Sci., Univ. of York, York, UK]"],"affiliations":[{"raw_affiliation_string":"[Dept. of Comput. Sci., Univ. of York, York, UK]","institution_ids":["https://openalex.org/I52099693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080547590","display_name":"Simon O\u2019Keefe","orcid":"https://orcid.org/0000-0001-5957-2474"},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Simon E. M. O'Keefe","raw_affiliation_strings":["[Dept. of Comput. Sci., Univ. of York, York, UK]"],"affiliations":[{"raw_affiliation_string":"[Dept. of Comput. Sci., Univ. of York, York, UK]","institution_ids":["https://openalex.org/I52099693"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.467,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":2,"citation_normalized_percentile":{"value":0.433699,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":71,"max":74},"biblio":{"volume":null,"issue":null,"first_page":"330","last_page":"335"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9914,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9914,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9884,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9862,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/spectrogram","display_name":"Spectrogram","score":0.8028037},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5852294}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.8028037},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.64896464},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.63589704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6196734},{"id":"https://openalex.org/C17095337","wikidata":"https://www.wikidata.org/wiki/Q2375229","display_name":"Piecewise linear function","level":2,"score":0.5867495},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5852294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48467544},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.443041},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37621394},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35560814},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33645454},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21665713},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.16266057},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12669533},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.062738925},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.05335328},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2009.84","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://eprints.whiterose.ac.uk/67984/1/Lampert09Multi_ScalePiecewise_LinearFeatureDetector.pdf","pdf_url":"https://eprints.whiterose.ac.uk/67984/1/Lampert09Multi_ScalePiecewise_LinearFeatureDetector.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":["White Rose University Consortium"],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://eprints.whiterose.ac.uk/67984/1/Lampert09Multi_ScalePiecewise_LinearFeatureDetector.pdf","pdf_url":"https://eprints.whiterose.ac.uk/67984/1/Lampert09Multi_ScalePiecewise_LinearFeatureDetector.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":["White Rose University Consortium"],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":19,"referenced_works":["https://openalex.org/W107968503","https://openalex.org/W1502099172","https://openalex.org/W169282377","https://openalex.org/W1903859743","https://openalex.org/W1949155057","https://openalex.org/W1988696798","https://openalex.org/W2039228789","https://openalex.org/W2045940966","https://openalex.org/W2061315086","https://openalex.org/W2088622959","https://openalex.org/W2092738703","https://openalex.org/W2095091350","https://openalex.org/W2114256817","https://openalex.org/W2120122557","https://openalex.org/W2799061466","https://openalex.org/W3037891630","https://openalex.org/W3165903168","https://openalex.org/W4244494905","https://openalex.org/W4253920039"],"related_works":["https://openalex.org/W4375868962","https://openalex.org/W3208509670","https://openalex.org/W3182827720","https://openalex.org/W2530685530","https://openalex.org/W2490196280","https://openalex.org/W2133947431","https://openalex.org/W2109304297","https://openalex.org/W2100864966","https://openalex.org/W2083709218","https://openalex.org/W1596838019"],"abstract_inverted_index":{"Reliable":[0],"feature":[1,38,75],"detection":[2,18,22,39,58,124],"is":[3,24,44,95,141],"a":[4,65,71,145],"prerequisite":[5],"to":[6,46,78,86,128],"higher":[7],"level":[8],"decisions":[9],"regarding":[10],"image":[11],"content.In":[12],"the":[13,21,42,87,98,108,117,132],"domain":[14],"of":[15,36,67,81,102,131],"spectrogram":[16],"track":[17,34],"and":[19,30,50,70],"classification,":[20],"problem":[23],"compounded":[25],"by":[26],"low":[27],"signal-to-noise":[28],"ratios":[29],"high":[31],"variation":[32],"in":[33,41,52,123],"appearance.Evaluation":[35],"standard":[37],"methods":[40,104,134],"literature":[43],"essential":[45],"determine":[47],"their":[48],"strengths":[49],"weaknesses":[51],"this":[53,55],"domain.With":[54],"knowledge,":[56],"improved":[57],"strategies":[59,90],"can":[60],"be":[61],"developed.This":[62],"paper":[63],"presents":[64],"comparison":[66],"line":[68],"detectors":[69],"novel,":[72],"multi-scale,":[73],"linear":[74],"detector":[76],"able":[77],"detect":[79],"tracks":[80],"varying":[82],"gradients.We":[83],"outline":[84],"improvements":[85],"multi-scale":[88,146],"search":[89],"which":[91],"reduce":[92],"runtime":[93],"costs.It":[94],"shown":[96,143],"that":[97,116,144],"Equal":[99],"Error":[100],"Rates":[101],"existing":[103],"are":[105],"high,":[106],"highlighting":[107],"need":[109],"for":[110],"research":[111],"into":[112],"novel":[113],"detectors.Results":[114],"demonstrate":[115],"proposed":[118],"method":[119],"offers":[120,148],"an":[121,149],"improvement":[122,150],"rates":[125,139],"when":[126],"compared":[127],"other,":[129],"state":[130],"art,":[133],"whilst":[135],"keeping":[136],"false":[137],"positive":[138],"low.It":[140],"also":[142],"implementation":[147],"over":[151],"fixed":[152],"scale":[153],"implementations.":[154]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2127628554","counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2024-12-24T13:55:20.705020","created_date":"2016-06-24"}