{"id":"https://openalex.org/W4367365651","doi":"https://doi.org/10.48550/arxiv.2304.13880","title":"Deep Learning Techniques for Hyperspectral Image Analysis in Agriculture: A Review","display_name":"Deep Learning Techniques for Hyperspectral Image Analysis in Agriculture: A Review","publication_year":2023,"publication_date":"2023-04-26","ids":{"openalex":"https://openalex.org/W4367365651","doi":"https://doi.org/10.48550/arxiv.2304.13880"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2304.13880","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.13880","pdf_url":"https://arxiv.org/pdf/2304.13880","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"review","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2304.13880","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071869510","display_name":"Mohamed Fadhlallah Guerri","orcid":"https://orcid.org/0000-0002-7567-6625"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Guerri, Mohamed Fadhlallah","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002571252","display_name":"Cosimo Distante","orcid":"https://orcid.org/0000-0002-1073-2390"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Distante, Cosimo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100781196","display_name":"P. Spagnolo","orcid":"https://orcid.org/0000-0001-7962-5203"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Spagnolo, Paolo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042700750","display_name":"Fares Bougourzi","orcid":"https://orcid.org/0000-0001-5077-4862"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bougourzi, Fares","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5106468368","display_name":"Abdelmalik Taleb\u2010Ahmed","orcid":"https://orcid.org/0000-0001-8750-1905"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taleb-Ahmed, Abdelmalik","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5071869510"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9896000027656555,"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":0.9896000027656555,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9695000052452087,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.9681000113487244,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9116239547729492},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7316167950630188},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6480340361595154},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6426339745521545},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5596860647201538},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5255476236343384},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5079277157783508},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4006659984588623},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35759204626083374},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.32313477993011475},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.25196540355682373},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10540342330932617}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9116239547729492},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7316167950630188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6480340361595154},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6426339745521545},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5596860647201538},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5255476236343384},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5079277157783508},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4006659984588623},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35759204626083374},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.32313477993011475},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.25196540355682373},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10540342330932617},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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":2,"locations":[{"id":"pmh:oai:arXiv.org:2304.13880","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.13880","pdf_url":"https://arxiv.org/pdf/2304.13880","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2304.13880","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2304.13880","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2304.13880","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.13880","pdf_url":"https://arxiv.org/pdf/2304.13880","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.7599999904632568,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[{"id":"https://openalex.org/G453067482","display_name":null,"funder_award_id":"014-2020","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"},{"id":"https://openalex.org/G5634946813","display_name":null,"funder_award_id":"2014-2020","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"}],"funders":[{"id":"https://openalex.org/F4320335322","display_name":"European Regional Development Fund","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4367365651.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W4380075502"],"abstract_inverted_index":{"In":[0],"the":[1,36],"recent":[2,69],"years,":[3],"hyperspectral":[4],"imaging":[5],"(HSI)":[6],"has":[7,102],"gained":[8],"considerably":[9],"popularity":[10],"among":[11],"computer":[12],"vision":[13],"researchers":[14],"for":[15],"its":[16],"potential":[17],"in":[18,24,62,95],"solving":[19],"remote":[20],"sensing":[21],"problems,":[22],"especially":[23],"agriculture":[25],"field.":[26],"However,":[27],"HSI":[28,63],"classification":[29],"is":[30],"a":[31],"complex":[32],"task":[33],"due":[34],"to":[35],"high":[37],"redundancy":[38],"of":[39,71,99],"spectral":[40,52],"bands,":[41],"limited":[42],"training":[43],"samples,":[44],"and":[45,51,83,91,105,117],"non-linear":[46],"relationship":[47],"between":[48],"spatial":[49],"position":[50],"bands.":[53],"Fortunately,":[54],"deep":[55,72],"learning":[56,73],"techniques":[57],"have":[58],"shown":[59],"promising":[60],"results":[61],"analysis.":[64],"This":[65],"literature":[66],"review":[67],"explores":[68],"applications":[70],"approaches":[74,101],"such":[75],"as":[76],"Autoencoders,":[77],"Convolutional":[78],"Neural":[79,86],"Networks":[80,94],"(1D,":[81],"2D,":[82],"3D),":[84],"Recurrent":[85],"Networks,":[87,90],"Deep":[88],"Belief":[89],"Generative":[92],"Adversarial":[93],"agriculture.":[96],"The":[97],"performance":[98],"these":[100],"been":[103],"evaluated":[104],"discussed":[106],"on":[107],"well-known":[108],"land":[109],"cover":[110],"datasets":[111],"including":[112],"Indian":[113],"Pines,":[114],"Salinas":[115],"Valley,":[116],"Pavia":[118],"University.":[119]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2023-04-30T00:00:00"}
