{"id":"https://openalex.org/W3010188879","doi":"https://doi.org/10.1109/icspcs47537.2019.9008719","title":"Extended Semi-Supervised Learning GAN for Hyperspectral Imagery Classification","display_name":"Extended Semi-Supervised Learning GAN for Hyperspectral Imagery Classification","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3010188879","doi":"https://doi.org/10.1109/icspcs47537.2019.9008719","mag":"3010188879"},"language":"en","primary_location":{"id":"doi:10.1109/icspcs47537.2019.9008719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcs47537.2019.9008719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS)","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/A5018983084","display_name":"Andrew D. Hahn","orcid":"https://orcid.org/0000-0002-0246-2108"},"institutions":[{"id":"https://openalex.org/I35364215","display_name":"Naval Postgraduate School","ror":"https://ror.org/033yfkj90","country_code":"US","type":"education","lineage":["https://openalex.org/I1330347796","https://openalex.org/I3130687028","https://openalex.org/I35364215"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andrew Hahn","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Naval Postgraduate School, Monterey, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Naval Postgraduate School, Monterey, CA, USA","institution_ids":["https://openalex.org/I35364215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111435850","display_name":"Murali Tummala","orcid":null},"institutions":[{"id":"https://openalex.org/I35364215","display_name":"Naval Postgraduate School","ror":"https://ror.org/033yfkj90","country_code":"US","type":"education","lineage":["https://openalex.org/I1330347796","https://openalex.org/I3130687028","https://openalex.org/I35364215"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Murali Tummala","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Naval Postgraduate School, Monterey, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Naval Postgraduate School, Monterey, CA, USA","institution_ids":["https://openalex.org/I35364215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039223176","display_name":"James Scrofani","orcid":null},"institutions":[{"id":"https://openalex.org/I35364215","display_name":"Naval Postgraduate School","ror":"https://ror.org/033yfkj90","country_code":"US","type":"education","lineage":["https://openalex.org/I1330347796","https://openalex.org/I3130687028","https://openalex.org/I35364215"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Scrofani","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Naval Postgraduate School, Monterey, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Naval Postgraduate School, Monterey, CA, USA","institution_ids":["https://openalex.org/I35364215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018983084"],"corresponding_institution_ids":["https://openalex.org/I35364215"],"apc_list":null,"apc_paid":null,"fwci":0.1012,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.48198198,"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":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994999766349792,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994999766349792,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9987000226974487,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9977999925613403,"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":0.811251163482666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7679845094680786},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7630631327629089},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6206312775611877},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6031821966171265},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5498290061950684},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5398094058036804},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4761276841163635},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.44882118701934814},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4364428222179413},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.4332715570926666},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19691139459609985},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08604875206947327}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.811251163482666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7679845094680786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7630631327629089},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6206312775611877},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6031821966171265},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5498290061950684},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5398094058036804},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4761276841163635},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.44882118701934814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4364428222179413},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.4332715570926666},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19691139459609985},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08604875206947327},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icspcs47537.2019.9008719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcs47537.2019.9008719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2099471712","https://openalex.org/W2125389028","https://openalex.org/W2173520492","https://openalex.org/W2549453541","https://openalex.org/W2772330423","https://openalex.org/W2777427437","https://openalex.org/W2791006446","https://openalex.org/W2963373786","https://openalex.org/W2963684088","https://openalex.org/W4235838711","https://openalex.org/W4320013936","https://openalex.org/W6678815747","https://openalex.org/W6685352114","https://openalex.org/W6718379498"],"related_works":["https://openalex.org/W2888032422","https://openalex.org/W2996316059","https://openalex.org/W2911497689","https://openalex.org/W2952813363","https://openalex.org/W4377980832","https://openalex.org/W4360783045","https://openalex.org/W2897769091","https://openalex.org/W2963346891","https://openalex.org/W3176438653","https://openalex.org/W2770149305"],"abstract_inverted_index":{"Hyperspectral":[0],"imagery":[1],"(HSI)":[2],"cubes":[3],"are":[4],"high-dimensional":[5],"datasets":[6],"that":[7],"lend":[8],"themselves":[9],"well":[10,101],"to":[11,28,75,88],"deep":[12],"learning":[13,18,58],"approaches":[14],"for":[15,61],"classification.":[16],"Deep":[17],"approaches,":[19],"specifically":[20],"generative":[21],"adversarial":[22],"networks":[23,99],"(GANs),":[24],"have":[25,85],"been":[26,86],"shown":[27],"be":[29],"very":[30],"effective":[31],"in":[32,40,93],"classification":[33,77,94],"and":[34,66],"generation":[35],"of":[36,49,70,78],"accurate":[37,105],"synthetic":[38,106],"data":[39],"computer":[41],"vision":[42],"problems.":[43],"This":[44],"work":[45],"proposes":[46],"an":[47,50],"extension":[48],"existing":[51],"GAN":[52,63],"training":[53,64,73],"scheme,":[54],"called":[55],"extended":[56],"semi-supervised":[57],"(ESSL),":[59],"metrics":[60],"evaluating":[62],"performance,":[65],"demonstrates":[67],"the":[68,71],"effectiveness":[69],"proposed":[72],"scheme":[74],"improve":[76],"HSI.":[79],"Using":[80],"ESSL":[81],"with":[82],"GAN,":[83],"we":[84],"able":[87],"achieve":[89],"approximately":[90],"0.8%":[91],"increase":[92],"accuracy":[95],"over":[96],"convolutional":[97],"neural":[98],"as":[100,102],"generate":[103],"extremely":[104],"imagery.":[107]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}