{"id":"https://openalex.org/W2786105573","doi":"https://doi.org/10.1109/icarm.2017.8273150","title":"A new framework of target detection in hyperspectral images","display_name":"A new framework of target detection in hyperspectral images","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2786105573","doi":"https://doi.org/10.1109/icarm.2017.8273150","mag":"2786105573"},"language":"en","primary_location":{"id":"doi:10.1109/icarm.2017.8273150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm.2017.8273150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 2nd International Conference on Advanced Robotics and Mechatronics (ICARM)","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/A5000124250","display_name":"Yanshan Li","orcid":"https://orcid.org/0000-0002-8814-4628"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanshan Li","raw_affiliation_strings":["College of Information Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031220055","display_name":"Jianjie Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]},{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianjie Xu","raw_affiliation_strings":["ATR National Key Lab. of Defense Technology, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"ATR National Key Lab. of Defense Technology, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086176807","display_name":"Yayuan Chen","orcid":"https://orcid.org/0000-0001-6714-8737"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]},{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yayuan Chen","raw_affiliation_strings":["College of Information Engineering, Shenzhen University, Shenzhen, China","School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088074415","display_name":"Zhoufan Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhoufan Kong","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066148256","display_name":"Qinghua Huang","orcid":"https://orcid.org/0000-0003-1080-6940"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Huang","raw_affiliation_strings":["College of Information Engineering, Shenzhen University, Shenzhen, China","School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","School of Electronics and Information, and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi'an, Shaanxi, PR China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"School of Electronics and Information, and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi'an, Shaanxi, PR China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5000124250"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.27699589,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"36","issue":null,"first_page":"144","last_page":"148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9824000000953674,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8362047672271729},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7358214855194092},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6749694347381592},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6201133728027344},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5850555300712585},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5232733488082886},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.48196670413017273},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46671172976493835},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4504745900630951},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4431779384613037},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43560490012168884},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4197729229927063},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.159382164478302}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8362047672271729},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7358214855194092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6749694347381592},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6201133728027344},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5850555300712585},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5232733488082886},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.48196670413017273},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46671172976493835},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4504745900630951},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4431779384613037},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43560490012168884},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4197729229927063},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.159382164478302},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarm.2017.8273150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm.2017.8273150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 2nd International Conference on Advanced Robotics and Mechatronics (ICARM)","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":29,"referenced_works":["https://openalex.org/W337593832","https://openalex.org/W1485235332","https://openalex.org/W1964134198","https://openalex.org/W1988920861","https://openalex.org/W1990579409","https://openalex.org/W2012743205","https://openalex.org/W2047870694","https://openalex.org/W2063253123","https://openalex.org/W2066931949","https://openalex.org/W2075925932","https://openalex.org/W2096038730","https://openalex.org/W2108333036","https://openalex.org/W2109836508","https://openalex.org/W2111072639","https://openalex.org/W2117741752","https://openalex.org/W2124571274","https://openalex.org/W2152057649","https://openalex.org/W2163352848","https://openalex.org/W2171521847","https://openalex.org/W2179290474","https://openalex.org/W2221390793","https://openalex.org/W2323049609","https://openalex.org/W2325343745","https://openalex.org/W2334249198","https://openalex.org/W2342598318","https://openalex.org/W2551662077","https://openalex.org/W6685336383","https://openalex.org/W6700819511","https://openalex.org/W6703260071"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2317401237","https://openalex.org/W1990800631","https://openalex.org/W2167120702","https://openalex.org/W2579567122"],"abstract_inverted_index":{"Hyperspectral":[0],"Image":[1],"(HSI)":[2],"is":[3,35,85,131,145,172],"used":[4,86],"widely":[5],"in":[6,10,38],"many":[7,117],"areas,":[8],"especially":[9],"the":[11,17,22,99,123,127,155,167,170,176,180,191],"remote":[12,19],"sensing":[13,20],"field.":[14],"Compared":[15],"with":[16,150,164],"traditional":[18,45,199],"HSI,":[21],"large-scale":[23],"and":[24,32,41,140],"high-resolution":[25,36],"HSI":[26],"(LHHSI)":[27],"which":[28,125],"has":[29,194],"big":[30],"data":[31],"large":[33],"size":[34],"both":[37],"spatial":[39],"domain":[40],"spectral":[42,89,114],"domain.":[43],"However,":[44],"methods":[46],"of":[47,63,83,91,116,179],"automatic":[48,64],"target":[49,65,110,129],"detection":[50,66],"do":[51],"not":[52],"apply":[53],"to":[54,87,104],"LHHSI.":[55],"Therefore,":[56],"this":[57],"paper":[58],"proposes":[59],"a":[60,148,195],"novel":[61],"framework":[62],"for":[67],"LHHSI":[68,84],"based":[69,153],"on":[70,154],"spatial-spectral":[71],"interest":[72],"point":[73],"(SSIP).":[74],"It":[75],"contains":[76,126],"five":[77],"key":[78,119],"steps.":[79],"Firstly,":[80],"bands":[81],"selection":[82],"reduce":[88],"dimension":[90],"LHHSIs.":[92,100],"Second,":[93],"we":[94,102,174],"extract":[95],"candidate":[96],"SSIPs":[97],"from":[98],"Third,":[101],"need":[103],"determine":[105],"whether":[106],"there":[107],"exist":[108],"potential":[109,128],"regions":[111,130],"by":[112,136,147],"using":[113,137],"curves":[115],"selected":[118,156],"SSIPs.":[120,157],"And":[121],"next,":[122],"image":[124,134,143,160],"divided":[132],"into":[133],"blocks":[135,161],"quad-tree":[138,177],"segmentation,":[139],"then":[141],"every":[142],"block":[144,182],"represented":[146],"vector":[149],"BoW":[151],"model":[152],"Finally,":[158],"these":[159],"are":[162],"classified":[163],"SVM.":[165],"During":[166],"classification,":[168],"if":[169],"result":[171],"what":[173],"need,":[175],"segmentation":[178],"current":[181],"will":[183],"be":[184],"ended.":[185],"The":[186],"experimental":[187],"results":[188],"show":[189],"that":[190],"proposed":[192],"algorithm":[193],"better":[196],"performance":[197],"than":[198],"algorithms.":[200]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
