{"id":"https://openalex.org/W2546490537","doi":"https://doi.org/10.1109/aipr.2012.6528195","title":"Centralized multi-scale singular value decomposition for feature construction in LIDAR image classification problems","display_name":"Centralized multi-scale singular value decomposition for feature construction in LIDAR image classification problems","publication_year":2012,"publication_date":"2012-10-01","ids":{"openalex":"https://openalex.org/W2546490537","doi":"https://doi.org/10.1109/aipr.2012.6528195","mag":"2546490537"},"language":"en","primary_location":{"id":"doi:10.1109/aipr.2012.6528195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2012.6528195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","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/A5063918137","display_name":"Devasis Bassu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"D. Bassu","raw_affiliation_strings":["Applied Communication Sciences, Basking Ridge, USA","Applied Communications Sciences, Inc., USA"],"affiliations":[{"raw_affiliation_string":"Applied Communication Sciences, Basking Ridge, USA","institution_ids":[]},{"raw_affiliation_string":"Applied Communications Sciences, Inc., USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078482977","display_name":"Rauf Izmailov","orcid":"https://orcid.org/0000-0002-7326-669X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R. Izmailov","raw_affiliation_strings":["Applied Communication Sciences, Basking Ridge, USA","Applied Communications Sciences, Inc., USA"],"affiliations":[{"raw_affiliation_string":"Applied Communication Sciences, Basking Ridge, USA","institution_ids":[]},{"raw_affiliation_string":"Applied Communications Sciences, Inc., USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056172120","display_name":"Allen McIntosh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. McIntosh","raw_affiliation_strings":["Applied Communication Sciences, Basking Ridge, USA","Applied Communications Sciences, Inc., USA"],"affiliations":[{"raw_affiliation_string":"Applied Communication Sciences, Basking Ridge, USA","institution_ids":[]},{"raw_affiliation_string":"Applied Communications Sciences, Inc., USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000561768","display_name":"Linda Ness","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"L. Ness","raw_affiliation_strings":["Applied Communication Sciences, Basking Ridge, USA","Applied Communications Sciences, Inc., USA"],"affiliations":[{"raw_affiliation_string":"Applied Communication Sciences, Basking Ridge, USA","institution_ids":[]},{"raw_affiliation_string":"Applied Communications Sciences, Inc., USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010057692","display_name":"David Shallcross","orcid":"https://orcid.org/0000-0003-0552-9758"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"D. Shallcross","raw_affiliation_strings":["Applied Communication Sciences, Basking Ridge, USA","Applied Communications Sciences, Inc., USA"],"affiliations":[{"raw_affiliation_string":"Applied Communication Sciences, Basking Ridge, USA","institution_ids":[]},{"raw_affiliation_string":"Applied Communications Sciences, Inc., USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5063918137"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5491,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.72119419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9948999881744385,"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/T10057","display_name":"Face and Expression Recognition","score":0.9948999881744385,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.992900013923645,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.6634339094161987},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6205360889434814},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6068730354309082},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5942755937576294},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.5309972763061523},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5293477177619934},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5101554989814758},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.5071358680725098},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5065237283706665},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.49559032917022705},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4360663890838623},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42228010296821594},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33511048555374146},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.326913058757782},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.24347659945487976},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.19227734208106995},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1811613142490387},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09925097227096558},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.07830899953842163}],"concepts":[{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.6634339094161987},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6205360889434814},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6068730354309082},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5942755937576294},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.5309972763061523},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5293477177619934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5101554989814758},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.5071358680725098},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5065237283706665},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.49559032917022705},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4360663890838623},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42228010296821594},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33511048555374146},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.326913058757782},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.24347659945487976},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.19227734208106995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1811613142490387},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09925097227096558},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.07830899953842163},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aipr.2012.6528195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2012.6528195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","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":19,"referenced_works":["https://openalex.org/W91088564","https://openalex.org/W140777655","https://openalex.org/W143703132","https://openalex.org/W214577476","https://openalex.org/W1570513731","https://openalex.org/W2046104068","https://openalex.org/W2074411795","https://openalex.org/W2107599050","https://openalex.org/W2116801843","https://openalex.org/W2119479037","https://openalex.org/W2127243551","https://openalex.org/W2140095548","https://openalex.org/W2148603752","https://openalex.org/W2161336914","https://openalex.org/W2911964244","https://openalex.org/W2963809831","https://openalex.org/W4213367101","https://openalex.org/W4251171122","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W4281783339","https://openalex.org/W1964041166","https://openalex.org/W4390887692","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Creation":[0],"and":[1,41,83,133,176,209],"selection":[2],"of":[3,20,32,39,46,104,112,115,145,151,197,205,220],"relevant":[4,51],"features":[5],"for":[6,130,213,224],"machine":[7],"learning":[8],"applications":[9],"(including":[10],"image":[11],"classification)":[12],"is":[13,24,154,167,186],"typically":[14],"a":[15,101,108,171,217],"process":[16,34],"requiring":[17],"significant":[18],"involvement":[19],"domain":[21],"knowledge.":[22],"It":[23],"thus":[25],"desirable":[26],"to":[27,52,61,99],"cover":[28],"at":[29],"least":[30],"part":[31],"that":[33,48,190],"with":[35,69,118,181],"semi-automated":[36],"techniques":[37],"capable":[38],"discovering":[40],"visualizing":[42],"those":[43],"geometric":[44],"characteristics":[45],"images":[47],"are":[49],"potentially":[50],"the":[53,80,148,177,191,206,221],"classification":[54,119,179,199,214],"objective.":[55],"In":[56],"this":[57,97,146],"work,":[58],"we":[59],"propose":[60],"utilize":[62],"multi-scale":[63,102],"singular":[64],"value":[65],"decomposition":[66],"(MSVD)":[67],"along":[68],"approximate":[70,139],"nearest":[71,140],"neighbors":[72],"algorithm:":[73],"both":[74],"have":[75],"been":[76],"recently":[77],"realized":[78],"using":[79,170],"randomized":[81],"approach,":[82],"can":[84],"be":[85],"efficiently":[86],"run":[87],"on":[88],"large,":[89],"high-dimensional":[90],"datasets":[91],"(sparse":[92],"or":[93],"dense).":[94],"We":[95,126],"apply":[96],"technique":[98],"create":[100],"view":[103],"every":[105,131],"point":[106,132],"in":[107],"publicly":[109],"available":[110],"set":[111,150],"LIDAR":[113],"data":[114,153],"riparian":[116],"images,":[117],"objective":[120],"being":[121],"separating":[122],"ground":[123],"from":[124],"vegetation.":[125],"perform":[127],"\u201ccentralized":[128],"MSVD\u201d":[129],"its":[134,198],"neighborhood":[135],"generated":[136,159],"by":[137,156,160],"an":[138],"neighbor":[141],"algorithm.":[142],"After":[143],"completion":[144],"procedure,":[147],"original":[149],"3-dimensional":[152],"augmented":[155],"36":[157],"dimensions":[158],"MSVD":[161,207],"(in":[162,195],"three":[163],"different":[164],"scales),":[165],"which":[166],"then":[168],"processed":[169],"novel":[172],"discretization":[173],"pre-processing":[174],"method":[175],"SVM":[178],"algorithm":[180],"RBF":[182],"kernel.":[183],"The":[184,202],"result":[185],"two":[187],"times":[188],"better":[189],"one":[192],"previously":[193],"obtained":[194],"terms":[196],"error":[200],"level).":[201],"generic":[203],"nature":[204],"mechanism":[208],"standard":[210],"mechanisms":[211],"used":[212],"(SVM)":[215],"suggest":[216],"wider":[218],"utility":[219],"proposed":[222],"approach":[223],"other":[225],"problems":[226],"as":[227],"well.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}