{"id":"https://openalex.org/W3198367078","doi":"https://doi.org/10.1145/3461353.3461387","title":"Anomaly Detection in Hyperspectral Image Based on SVDD Combined with Features Compression","display_name":"Anomaly Detection in Hyperspectral Image Based on SVDD Combined with Features Compression","publication_year":2021,"publication_date":"2021-03-05","ids":{"openalex":"https://openalex.org/W3198367078","doi":"https://doi.org/10.1145/3461353.3461387","mag":"3198367078"},"language":"en","primary_location":{"id":"doi:10.1145/3461353.3461387","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3461353.3461387","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 the 5th International Conference on Innovation in Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","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/A5020056534","display_name":"Ping Ma","orcid":"https://orcid.org/0000-0003-3687-364X"},"institutions":[{"id":"https://openalex.org/I134738993","display_name":"Shandong University of Traditional Chinese Medicine","ror":"https://ror.org/0523y5c19","country_code":"CN","type":"education","lineage":["https://openalex.org/I134738993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Ma","raw_affiliation_strings":["Shandong University of Traditional Chinese Medicine, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University of Traditional Chinese Medicine, China","institution_ids":["https://openalex.org/I134738993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015497483","display_name":"Chengfei Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengfei Yao","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences), China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences), China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101533089","display_name":"Yang Li","orcid":"https://orcid.org/0009-0003-0943-661X"},"institutions":[{"id":"https://openalex.org/I134738993","display_name":"Shandong University of Traditional Chinese Medicine","ror":"https://ror.org/0523y5c19","country_code":"CN","type":"education","lineage":["https://openalex.org/I134738993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["Shandong University of Traditional Chinese Medicine, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University of Traditional Chinese Medicine, China","institution_ids":["https://openalex.org/I134738993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113747303","display_name":"Jingang Ma","orcid":"https://orcid.org/0009-0002-3829-9039"},"institutions":[{"id":"https://openalex.org/I134738993","display_name":"Shandong University of Traditional Chinese Medicine","ror":"https://ror.org/0523y5c19","country_code":"CN","type":"education","lineage":["https://openalex.org/I134738993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingang Ma","raw_affiliation_strings":["Shandong University of Traditional Chinese Medicine, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University of Traditional Chinese Medicine, China","institution_ids":["https://openalex.org/I134738993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0876,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.76143387,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"103","last_page":"107"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962000250816345,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9674999713897705,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.897097647190094},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8426220417022705},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7334387898445129},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7204537391662598},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.702818751335144},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6731415390968323},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6352686285972595},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5896796584129333},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4620700478553772},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.43988174200057983},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.439582884311676},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37898528575897217},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.22332000732421875}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.897097647190094},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8426220417022705},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7334387898445129},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7204537391662598},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.702818751335144},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6731415390968323},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6352686285972595},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5896796584129333},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4620700478553772},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.43988174200057983},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.439582884311676},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37898528575897217},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.22332000732421875},{"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/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3461353.3461387","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3461353.3461387","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 the 5th International Conference on Innovation in Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1969781607","https://openalex.org/W1970088130","https://openalex.org/W1997866865","https://openalex.org/W2024288510","https://openalex.org/W2047870694","https://openalex.org/W2100921418","https://openalex.org/W2122646361","https://openalex.org/W2142552707","https://openalex.org/W2145962650","https://openalex.org/W2288752886","https://openalex.org/W2295576075","https://openalex.org/W3023114228"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W3194885736","https://openalex.org/W4363671829","https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2912112202"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,31,55,62,133],"in":[2,11,19,33,53,64],"hyperspectral":[3,34,65,82],"image":[4,35,66,83],"has":[5,16,146],"been":[6],"a":[7,44],"research":[8],"hot":[9],"topic":[10],"recent":[12],"years,":[13],"and":[14,26,75],"it":[15],"rich":[17],"applications":[18],"many":[20],"fields,":[21],"such":[22],"as":[23,109],"disaster":[24],"warning":[25],"military":[27],"reconnaissance.":[28],"Traditional":[29],"anomaly":[30,61,132],"methods":[32],"usually":[36],"need":[37],"to":[38,86,119,129],"assume":[39],"that":[40,142],"the":[41,93,99,105,110,114,121,143],"data":[42],"fits":[43],"certain":[45],"distribution":[46],"or":[47],"use":[48],"low-order":[49],"statistical":[50],"features,":[51],"resulting":[52],"poor":[54],"accuracy.":[56],"This":[57],"paper":[58],"proposes":[59],"an":[60,88,131],"method":[63,125,145],"based":[67],"on":[68,138],"SVDD":[69],"combined":[70],"with":[71,151],"nonlinear":[72],"feature":[73,76,116],"mapping":[74],"compression.":[77],"The":[78,90,102,123,135],"selected":[79],"bands":[80],"of":[81,92,104],"are":[84,95],"used":[85,118],"construct":[87,130],"autoencoder.":[89],"parameters":[91],"autoencoder":[94],"adjusted":[96],"by":[97],"minimizing":[98],"reconstruction":[100],"error.":[101],"output":[103],"encoder":[106],"is":[107,117],"regarded":[108],"compressed":[111,115],"feature.":[112],"Then":[113],"train":[120],"SVDD.":[122],"proposed":[124,144],"uses":[126],"fewer":[127],"features":[128],"model.":[134],"experimental":[136],"results":[137,149],"real":[139],"datasets":[140],"show":[141],"achieved":[147],"outstanding":[148],"compared":[150],"other":[152],"state-of-the-art":[153],"methods.":[154]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
