{"id":"https://openalex.org/W4376852344","doi":"https://doi.org/10.1145/3573942.3574108","title":"Hyperspectral Anomaly Detection based on Autoencoder using Superpixel Manifold Constraint","display_name":"Hyperspectral Anomaly Detection based on Autoencoder using Superpixel Manifold Constraint","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4376852344","doi":"https://doi.org/10.1145/3573942.3574108"},"language":"en","primary_location":{"id":"doi:10.1145/3573942.3574108","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3573942.3574108","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","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/A5082633003","display_name":"Yuquan Gan","orcid":"https://orcid.org/0000-0002-1093-6502"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuquan Gan","raw_affiliation_strings":["School of Telecommunication and Information Engineering,Center for Image and Information Processing,Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-1093-6502","affiliations":[{"raw_affiliation_string":"School of Telecommunication and Information Engineering,Center for Image and Information Processing,Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103057934","display_name":"Wenqiang Li","orcid":"https://orcid.org/0000-0002-8427-7976"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqiang Li","raw_affiliation_strings":["School of Telecommunication and Information Engineering,Center for Image and Information Processing,Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-8427-7976","affiliations":[{"raw_affiliation_string":"School of Telecommunication and Information Engineering,Center for Image and Information Processing,Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100761763","display_name":"Ying Liu","orcid":"https://orcid.org/0000-0002-9037-7818"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Liu","raw_affiliation_strings":["School of Telecommunication and Information Engineering,Center for Image and Information Processing,Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-9037-7818","affiliations":[{"raw_affiliation_string":"School of Telecommunication and Information Engineering,Center for Image and Information Processing,Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035149071","display_name":"Jinglu He","orcid":"https://orcid.org/0000-0003-3869-0556"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinglu He","raw_affiliation_strings":["School of Telecommunication and Information Engineering,Center for Image and Information Processing,Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0003-3869-0556","affiliations":[{"raw_affiliation_string":"School of Telecommunication and Information Engineering,Center for Image and Information Processing,Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100705326","display_name":"Ji Zhang","orcid":"https://orcid.org/0000-0001-7167-6970"},"institutions":[{"id":"https://openalex.org/I185523456","display_name":"University of Southern Queensland","ror":"https://ror.org/04sjbnx57","country_code":"AU","type":"education","lineage":["https://openalex.org/I185523456"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ji Zhang","raw_affiliation_strings":["University of Southern Queensland,, Australia"],"raw_orcid":"https://orcid.org/0000-0001-7167-6970","affiliations":[{"raw_affiliation_string":"University of Southern Queensland,, Australia","institution_ids":["https://openalex.org/I185523456"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5082633003"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27037665,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"92","issue":null,"first_page":"873","last_page":"879"},"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":0.9368000030517578,"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":0.9113709926605225},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8358253240585327},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7865502834320068},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7686470746994019},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7525249719619751},{"id":"https://openalex.org/keywords/manifold-alignment","display_name":"Manifold alignment","score":0.7227470278739929},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5931037068367004},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5283616185188293},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.5122203230857849},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4929938018321991},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.48607924580574036},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.432931125164032},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.430563747882843},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.43041667342185974},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3968515694141388},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2908663749694824},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2873741388320923},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.2567695677280426},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08709707856178284}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9113709926605225},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8358253240585327},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7865502834320068},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7686470746994019},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7525249719619751},{"id":"https://openalex.org/C153120616","wikidata":"https://www.wikidata.org/wiki/Q17068315","display_name":"Manifold alignment","level":4,"score":0.7227470278739929},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5931037068367004},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5283616185188293},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.5122203230857849},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4929938018321991},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.48607924580574036},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.432931125164032},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.430563747882843},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.43041667342185974},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3968515694141388},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2908663749694824},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2873741388320923},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.2567695677280426},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08709707856178284},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3573942.3574108","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3573942.3574108","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","score":0.41999998688697815,"display_name":"No poverty"}],"awards":[{"id":"https://openalex.org/G8958005214","display_name":null,"funder_award_id":"2022JQ-668","funder_id":"https://openalex.org/F4320324173","funder_display_name":"Natural Science Foundation of Shaanxi Province"}],"funders":[{"id":"https://openalex.org/F4320324173","display_name":"Natural Science Foundation of Shaanxi Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2019287283","https://openalex.org/W2807662216","https://openalex.org/W2914584698","https://openalex.org/W2951559873","https://openalex.org/W4254373586"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W3194885736","https://openalex.org/W4363671829","https://openalex.org/W2355395139","https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W3109610583","https://openalex.org/W2387045723","https://openalex.org/W2375518579","https://openalex.org/W4281663961"],"abstract_inverted_index":{"In":[0],"the":[1,30,35,40,79,82,87,95,101,104,111,115,121,124,131,144,154,159],"field":[2],"of":[3,34,81,123,130,143],"hyperspectral":[4,58,83,132,168],"anomaly":[5,59,169],"detection,":[6],"autoencoder":[7,112],"(AE)":[8],"have":[9],"become":[10],"a":[11,57],"hot":[12],"research":[13],"topic":[14],"due":[15],"to":[16,77,93,113],"their":[17],"unsupervised":[18],"characteristics":[19],"and":[20,43,85,127,153],"powerful":[21],"feature":[22],"extraction":[23],"capability.":[24],"However,":[25],"autoencoders":[26,64],"do":[27],"not":[28],"keep":[29],"spatial":[31,126],"structure":[32,129],"information":[33],"original":[36],"data":[37],"well":[38],"during":[39],"training":[41],"process,":[42],"is":[44,69,75,91],"affected":[45],"by":[46,139],"anomalies,":[47],"resulting":[48],"in":[49,110],"poor":[50],"detection":[51,60,164],"performance.":[52],"To":[53],"address":[54],"these":[55],"problems,":[56],"method":[61,90,161],"based":[62,99],"on":[63,100,150],"with":[65],"superpixel":[66,72],"manifold":[67,88,97,106],"constraints":[68,107],"proposed.":[70],"Firstly,":[71],"segmentation":[73],"technique":[74],"used":[76,92],"obtain":[78],"superpixels":[80],"image,":[84],"then":[86],"learning":[89],"learn":[94,114],"embedded":[96,109],"that":[98,158],"superpixels.":[102],"Secondly,":[103],"learned":[105],"are":[108,137,148],"potential":[116],"representation,":[117],"which":[118],"can":[119],"maintain":[120],"consistency":[122],"local":[125],"geometric":[128],"images":[133],"(HSI).":[134],"Finally,":[135],"anomalies":[136],"detected":[138],"computing":[140],"reconstruction":[141],"errors":[142],"autoencoder.":[145],"Extensive":[146],"experiments":[147],"conducted":[149],"three":[151],"datasets,":[152],"experimental":[155],"results":[156],"show":[157],"proposed":[160],"has":[162],"better":[163],"performance":[165],"than":[166],"other":[167],"detectors.":[170]},"counts_by_year":[],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}
