{"id":"https://openalex.org/W7125982371","doi":"https://doi.org/10.1109/commnet68224.2025.11288910","title":"Hybrid 2D\u20133D Convolutional Neural Network for Hyperspectral Land-Cover Classification","display_name":"Hybrid 2D\u20133D Convolutional Neural Network for Hyperspectral Land-Cover Classification","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W7125982371","doi":"https://doi.org/10.1109/commnet68224.2025.11288910"},"language":null,"primary_location":{"id":"doi:10.1109/commnet68224.2025.11288910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/commnet68224.2025.11288910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 8th International Conference on Advanced Communication Technologies and Networking (CommNet)","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/A5114358418","display_name":"Assia Nouna","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145365","display_name":"Universit\u00e9 Hassan 1er","ror":"https://ror.org/03cdvht47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210145365"]}],"countries":["MA"],"is_corresponding":true,"raw_author_name":"Assia Nouna","raw_affiliation_strings":["Laboratory LAMSAD,ENSA, Hassan First University of Settat,Berrechid,Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory LAMSAD,ENSA, Hassan First University of Settat,Berrechid,Morocco","institution_ids":["https://openalex.org/I4210145365"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114358417","display_name":"Soumaya Nouna","orcid":"https://orcid.org/0000-0002-5733-1631"},"institutions":[{"id":"https://openalex.org/I4210145365","display_name":"Universit\u00e9 Hassan 1er","ror":"https://ror.org/03cdvht47","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210145365"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Soumaya Nouna","raw_affiliation_strings":["Laboratory LAMSAD,ENSA, Hassan First University of Settat,Berrechid,Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory LAMSAD,ENSA, Hassan First University of Settat,Berrechid,Morocco","institution_ids":["https://openalex.org/I4210145365"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092558648","display_name":"Ilyas Tammouch","orcid":"https://orcid.org/0000-0003-2752-4413"},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Ilyas Tammouch","raw_affiliation_strings":["Laboratory SETIME, Faculty of Science, Ibn Tofail University,Kenitra,Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory SETIME, Faculty of Science, Ibn Tofail University,Kenitra,Morocco","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5092558649","display_name":"Abdelamine Elouafi","orcid":"https://orcid.org/0009-0002-5877-2997"},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Abdelamine Elouafi","raw_affiliation_strings":["Laboratory SETIME, Faculty of Science, Ibn Tofail University,Kenitra,Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory SETIME, Faculty of Science, Ibn Tofail University,Kenitra,Morocco","institution_ids":["https://openalex.org/I3121676899"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5114358418"],"corresponding_institution_ids":["https://openalex.org/I4210145365"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68785906,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9825000166893005,"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":0.9825000166893005,"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":0.00419999985024333,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.0019000000320374966,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7459999918937683},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7056999802589417},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6865000128746033},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5584999918937683},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5414999723434448},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4797999858856201},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4578000009059906}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7459999918937683},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7281000018119812},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7056999802589417},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6865000128746033},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6747000217437744},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5584999918937683},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5414999723434448},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4797999858856201},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4578000009059906},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4163999855518341},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.3790999948978424},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3499999940395355},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3253999948501587},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.27379998564720154}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/commnet68224.2025.11288910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/commnet68224.2025.11288910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 8th International Conference on Advanced Communication Technologies and Networking (CommNet)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.4339908957481384,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1,94],"(HSI)":[2],"classification":[3],"faces":[4],"multiple":[5],"challenges":[6],"because":[7,44],"it":[8,138],"deals":[9],"with":[10,83,156],"extensive":[11],"spectral":[12,49,101,165],"data":[13,54],"which":[14,56,71,115],"creates":[15],"intricate":[16],"patterns":[17],"between":[18],"different":[19],"bands":[20],"and":[21,50,74,103,136,167],"complex":[22],"spatial":[23,51,80,91,104],"differences":[24,166],"in":[25],"scenes":[26],"that":[27,162],"shallow":[28],"classifiers":[29],"struggle":[30],"to":[31,78],"handle.":[32],"The":[33,64,87,109,148],"technology":[34],"of":[35,119],"convolutional":[36,76],"neural":[37],"networks":[38],"(CNNs)":[39],"offers":[40],"an":[41],"effective":[42],"solution":[43],"these":[45],"models":[46],"learn":[47],"hierarchical":[48],"features":[52,92],"through":[53,106,122],"analysis":[55],"eliminates":[57],"the":[58,97,117,129,132],"need":[59],"for":[60],"human\u2013designed":[61],"feature":[62],"extraction.":[63],"research":[65],"introduces":[66],"a":[67,112],"hybrid":[68,149],"CNN":[69],"model":[70,130],"combines":[72],"2D":[73,88],"3D":[75,98],"operations":[77],"process":[79],"information":[81,102],"together":[82,155],"spectral\u2013spatial":[84],"structural":[85],"data.":[86],"branch":[89,99],"extracts":[90],"from":[93],"patches":[95],"yet":[96],"analyzes":[100],"relationships":[105],"spectral-spatial":[107],"cubes.":[108],"system":[110],"generates":[111],"combined":[113],"representation":[114],"unites":[116],"advantages":[118],"both":[120],"streams":[121],"its":[123],"late":[124],"fusion":[125],"approach.":[126],"We":[127],"evaluate":[128],"on":[131],"Salinas":[133],"HSI":[134],"benchmark":[135],"compare":[137],"against":[139],"conventional":[140],"machine\u2013":[141],"learning":[142],"baselines":[143],"(e.g.,":[144],"KNN,":[145],"SVM,":[146],"RF).":[147],"network":[150],"reaches":[151],"better":[152],"overall":[153],"accuracy":[154],"enhanced":[157],"stability":[158],"when":[159],"handling":[160],"classes":[161],"show":[163],"small":[164],"complicated":[168],"texture":[169],"patterns.":[170]},"counts_by_year":[],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2026-01-29T00:00:00"}
