{"id":"https://openalex.org/W2008798127","doi":"https://doi.org/10.1109/mlsp.2012.6349724","title":"Haussdorff and hellinger for colorimetric sensor array classification","display_name":"Haussdorff and hellinger for colorimetric sensor array classification","publication_year":2012,"publication_date":"2012-09-01","ids":{"openalex":"https://openalex.org/W2008798127","doi":"https://doi.org/10.1109/mlsp.2012.6349724","mag":"2008798127"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2012.6349724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2012.6349724","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Workshop on Machine Learning for Signal Processing","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/A5064146030","display_name":"Tommy Sonne Alstr\u00f8m","orcid":"https://orcid.org/0000-0003-0941-3146"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Tommy S. Alstrom","raw_affiliation_strings":["Dept. of Informatics and Mathematical Modeling, Technical University of Denmark, Asmussens All\u00e9 321, 2800 Kgs. Lyngby, Denmark"],"affiliations":[{"raw_affiliation_string":"Dept. of Informatics and Mathematical Modeling, Technical University of Denmark, Asmussens All\u00e9 321, 2800 Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048873240","display_name":"Bj\u00f8rn Sand Jensen","orcid":"https://orcid.org/0000-0001-8074-228X"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Bjorn S. Jensen","raw_affiliation_strings":["Department of Informatics and Mathematical Modeling, Technical University of Denmark, Kongens Lyngby, Denmark","Dept. of Informatics and Mathematical Modeling, Technical University of Denmark, Asmussens All\u00e9 321, 2800 Kgs. Lyngby, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Informatics and Mathematical Modeling, Technical University of Denmark, Kongens Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]},{"raw_affiliation_string":"Dept. of Informatics and Mathematical Modeling, Technical University of Denmark, Asmussens All\u00e9 321, 2800 Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073902328","display_name":"Mikkel N. Schmidt","orcid":"https://orcid.org/0000-0001-6927-8869"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Mikkel N. Schmidt","raw_affiliation_strings":["Department of Informatics and Mathematical Modeling, Technical University of Denmark, Kongens Lyngby, Denmark","Dept. of Informatics and Mathematical Modeling, Technical University of Denmark, Asmussens All\u00e9 321, 2800 Kgs. Lyngby, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Informatics and Mathematical Modeling, Technical University of Denmark, Kongens Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]},{"raw_affiliation_string":"Dept. of Informatics and Mathematical Modeling, Technical University of Denmark, Asmussens All\u00e9 321, 2800 Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081856736","display_name":"Natalie Kostesha","orcid":null},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Natalie V. Kostesha","raw_affiliation_strings":["Department of Micro-and Nanotechnology, Technical University of Denmark, Kongens Lyngby, Denmark","Department of Micro and Nanotechnology, Technical University of Denmark, \u00d8rsteds Plads 345 east,DK-2800 Kgs. Lyngby,Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Micro-and Nanotechnology, Technical University of Denmark, Kongens Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]},{"raw_affiliation_string":"Department of Micro and Nanotechnology, Technical University of Denmark, \u00d8rsteds Plads 345 east,DK-2800 Kgs. Lyngby,Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070673552","display_name":"Jan Larsen","orcid":"https://orcid.org/0000-0003-1880-1810"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Jan Larsen","raw_affiliation_strings":["Department of Informatics and Mathematical Modeling, Technical University of Denmark, Kongens Lyngby, Denmark","Dept. of Informatics and Mathematical Modeling, Technical University of Denmark, Asmussens All\u00e9 321, 2800 Kgs. Lyngby, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Informatics and Mathematical Modeling, Technical University of Denmark, Kongens Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]},{"raw_affiliation_string":"Dept. of Informatics and Mathematical Modeling, Technical University of Denmark, Asmussens All\u00e9 321, 2800 Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5064146030"],"corresponding_institution_ids":["https://openalex.org/I96673099"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08473898,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9837999939918518,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9269000291824341,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hellinger-distance","display_name":"Hellinger distance","score":0.7304335236549377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6344822645187378},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6293061971664429},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6014652848243713},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5336592793464661},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.48667556047439575},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.48450610041618347},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.46784529089927673},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.43590012192726135},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4234694540500641},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3998434543609619},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2075149118900299},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16998019814491272},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09065908193588257}],"concepts":[{"id":"https://openalex.org/C153024298","wikidata":"https://www.wikidata.org/wiki/Q3030678","display_name":"Hellinger distance","level":2,"score":0.7304335236549377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6344822645187378},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6293061971664429},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6014652848243713},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5336592793464661},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.48667556047439575},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.48450610041618347},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.46784529089927673},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.43590012192726135},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4234694540500641},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3998434543609619},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2075149118900299},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16998019814491272},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09065908193588257},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"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/mlsp.2012.6349724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2012.6349724","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Workshop on Machine Learning for Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.gla.ac.uk:119577","is_oa":false,"landing_page_url":"http://eprints.gla.ac.uk/119577/","pdf_url":null,"source":{"id":"https://openalex.org/S4210235606","display_name":"ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)","issn_l":"2622-8912","issn":["2622-8912","2622-8920"],"is_oa":false,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1587670653","https://openalex.org/W1663973292","https://openalex.org/W1746819321","https://openalex.org/W1987828648","https://openalex.org/W1994567799","https://openalex.org/W2004894272","https://openalex.org/W2017986229","https://openalex.org/W2029047301","https://openalex.org/W2065286382","https://openalex.org/W2084413241","https://openalex.org/W2091850769","https://openalex.org/W2103375079","https://openalex.org/W2105381419","https://openalex.org/W2107105977","https://openalex.org/W2109743529","https://openalex.org/W2142011304","https://openalex.org/W2151531457","https://openalex.org/W2156080065","https://openalex.org/W2157219769","https://openalex.org/W2157516857","https://openalex.org/W2170265393","https://openalex.org/W2949683059","https://openalex.org/W3003413895","https://openalex.org/W4211049957","https://openalex.org/W6635172214","https://openalex.org/W6682443497"],"related_works":["https://openalex.org/W2050620380","https://openalex.org/W1977834563","https://openalex.org/W1979265735","https://openalex.org/W4390831585","https://openalex.org/W2057424919","https://openalex.org/W3097851170","https://openalex.org/W4385216087","https://openalex.org/W4406879792","https://openalex.org/W3157595377","https://openalex.org/W2153363506"],"abstract_inverted_index":{"Development":[0],"of":[1,7,45,47,97,119,129],"sensors":[2,58],"and":[3,22,36,50,80,101,126],"systems":[4],"for":[5,52,105],"detection":[6],"chemical":[8,128],"compounds":[9],"is":[10,31],"an":[11],"important":[12],"challenge":[13],"with":[14],"applications":[15],"in":[16,108],"areas":[17],"such":[18],"as":[19],"anti-terrorism,":[20],"demining,":[21],"environmental":[23],"monitoring.":[24],"A":[25],"newly":[26],"developed":[27,61],"colorimetric":[28],"sensor":[29,42,106,125],"array":[30],"able":[32],"to":[33,62],"detect":[34],"explosives":[35],"volatile":[37],"organic":[38],"compounds;":[39],"however,":[40],"each":[41],"reading":[43],"consists":[44],"hundreds":[46],"pixel":[48],"values,":[49],"methods":[51],"combining":[53],"these":[54],"readings":[55],"from":[56],"multiple":[57],"must":[59],"be":[60],"make":[63],"a":[64,89,95,103],"classification":[65,75],"system.":[66],"In":[67],"this":[68],"work":[69],"we":[70],"examine":[71],"two":[72],"distance":[73,91,99,120],"based":[74],"methods,":[76],"K-Nearest":[77],"Neighbor":[78],"(KNN)":[79],"Gaussian":[81],"process":[82],"(GP)":[83],"classification,":[84],"which":[85],"both":[86],"rely":[87],"on":[88,123],"suitable":[90],"metric.":[92],"We":[93],"evaluate":[94],"range":[96],"different":[98],"measures":[100],"propose":[102],"method":[104],"fusion":[107],"the":[109,116,124,127],"GP":[110],"classifier.":[111],"Our":[112],"results":[113],"indicate":[114],"that":[115],"best":[117],"choice":[118],"measure":[121],"depends":[122],"interest.":[130]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}