{"id":"https://openalex.org/W4206342541","doi":"https://doi.org/10.1145/3484824.3484884","title":"Deep Learning-Based Models for Classification of Invasive Plant Species from Hyperspectral Remotely Sensed Data","display_name":"Deep Learning-Based Models for Classification of Invasive Plant Species from Hyperspectral Remotely Sensed Data","publication_year":2021,"publication_date":"2021-08-09","ids":{"openalex":"https://openalex.org/W4206342541","doi":"https://doi.org/10.1145/3484824.3484884"},"language":"en","primary_location":{"id":"doi:10.1145/3484824.3484884","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3484824.3484884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Data Science, Machine Learning and Artificial Intelligence","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/A5001936210","display_name":"Abdulla A. Omeer","orcid":null},"institutions":[{"id":"https://openalex.org/I165259314","display_name":"Dr. Babasaheb Ambedkar Marathwada University","ror":"https://ror.org/033pfj584","country_code":"IN","type":"education","lineage":["https://openalex.org/I165259314"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Abdulla A. Omeer","raw_affiliation_strings":["Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, MH, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, MH, India","institution_ids":["https://openalex.org/I165259314"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002888610","display_name":"Ratnadeep R. Deshmukh","orcid":"https://orcid.org/0000-0002-1257-2300"},"institutions":[{"id":"https://openalex.org/I165259314","display_name":"Dr. Babasaheb Ambedkar Marathwada University","ror":"https://ror.org/033pfj584","country_code":"IN","type":"education","lineage":["https://openalex.org/I165259314"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ratnadeep R. Deshmukh","raw_affiliation_strings":["Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, MH, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, MH, India","institution_ids":["https://openalex.org/I165259314"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001936210"],"corresponding_institution_ids":["https://openalex.org/I165259314"],"apc_list":null,"apc_paid":null,"fwci":0.1652,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59774701,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"222","last_page":"230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9951000213623047,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9951000213623047,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9936000108718872,"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/T10616","display_name":"Smart Agriculture and AI","score":0.9677000045776367,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8250994682312012},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7546157836914062},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.740863561630249},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7394137978553772},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6845616698265076},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6719859838485718},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5501641631126404},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5295047760009766},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5198688507080078},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4899539053440094},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.405276358127594},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3278881311416626},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.14148077368736267}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8250994682312012},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7546157836914062},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.740863561630249},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7394137978553772},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6845616698265076},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6719859838485718},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5501641631126404},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5295047760009766},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5198688507080078},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4899539053440094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.405276358127594},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3278881311416626},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.14148077368736267}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3484824.3484884","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3484824.3484884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Data Science, Machine Learning and Artificial Intelligence","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":55,"referenced_works":["https://openalex.org/W273955616","https://openalex.org/W1520812622","https://openalex.org/W1558306512","https://openalex.org/W1563088657","https://openalex.org/W1958291604","https://openalex.org/W1976381494","https://openalex.org/W1996721947","https://openalex.org/W1999572825","https://openalex.org/W2002987700","https://openalex.org/W2010515061","https://openalex.org/W2012688023","https://openalex.org/W2029316659","https://openalex.org/W2045100235","https://openalex.org/W2054440265","https://openalex.org/W2086243902","https://openalex.org/W2092126505","https://openalex.org/W2097117768","https://openalex.org/W2098057602","https://openalex.org/W2101280078","https://openalex.org/W2103094532","https://openalex.org/W2109191549","https://openalex.org/W2138583748","https://openalex.org/W2153747028","https://openalex.org/W2155621630","https://openalex.org/W2156909104","https://openalex.org/W2162698522","https://openalex.org/W2166307050","https://openalex.org/W2167886224","https://openalex.org/W2249781099","https://openalex.org/W2314785379","https://openalex.org/W2330820318","https://openalex.org/W2431738724","https://openalex.org/W2572303978","https://openalex.org/W2574060215","https://openalex.org/W2604086375","https://openalex.org/W2624262830","https://openalex.org/W2756833625","https://openalex.org/W2792827505","https://openalex.org/W2808823242","https://openalex.org/W2901117552","https://openalex.org/W2903091095","https://openalex.org/W2911620309","https://openalex.org/W2963659230","https://openalex.org/W2964287450","https://openalex.org/W2991615914","https://openalex.org/W2996995115","https://openalex.org/W2998768810","https://openalex.org/W3005383134","https://openalex.org/W3014041368","https://openalex.org/W3094988652","https://openalex.org/W3102127038","https://openalex.org/W6610017368","https://openalex.org/W6631190155","https://openalex.org/W6635446068","https://openalex.org/W6674914833"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W3034375524","https://openalex.org/W4200112873","https://openalex.org/W2955796858","https://openalex.org/W4224941037","https://openalex.org/W2004826645","https://openalex.org/W4372048956","https://openalex.org/W3135818052","https://openalex.org/W3192962470"],"abstract_inverted_index":{"Invasive":[0],"plant":[1,51],"species":[2],"are":[3],"plants,":[4],"which":[5],"spread":[6],"extensively":[7],"outside":[8],"their":[9],"native":[10],"ecosystem.":[11],"They":[12],"pose":[13],"a":[14],"threat":[15],"to":[16,35],"the":[17,89,95,103,108,119,122,144,150],"environment":[18],"and":[19,23,29,71,102,117,135,160],"economy":[20],"at":[21],"global":[22],"local":[24],"scales,":[25],"making":[26],"effective":[27],"mapping":[28],"detecting":[30],"essential.":[31],"This":[32],"study":[33],"aims":[34],"develop":[36],"deep":[37,83],"neural":[38,84,98],"network-based":[39],"classification":[40],"models":[41,124,152],"for":[42],"hyperspectral":[43],"data.":[44],"The":[45,140],"spectral":[46],"reflectance":[47],"of":[48,82,121,158,163],"ten":[49],"invasive":[50],"leaves":[52],"was":[53],"collected":[54,63],"using":[55],"ASD":[56],"FieldSpec4":[57],"standard":[58],"Hi-Res":[59],"device.":[60],"Samples":[61],"were":[62,87],"from":[64],"Dr.":[65],"Babasaheb":[66],"Ambedkar":[67],"Marathwada":[68],"university":[69],"campus":[70],"Himayat":[72],"Bagh":[73],"garden":[74],"in":[75],"Aurangabad":[76],"city,":[77],"Maharashtra,":[78],"India.":[79],"Two":[80],"types":[81],"networks":[85],"(DNN)":[86],"applied:":[88],"first":[90],"one":[91],"is":[92,105],"based":[93,106],"on":[94,107],"one-dimensional":[96],"convolutional":[97,109],"network":[99],"(1D":[100],"CNN),":[101],"second":[104],"long":[110],"short":[111],"term":[112],"memory":[113],"(CNN-LSTM).":[114],"We":[115],"proposed":[116],"compare":[118],"performance":[120],"two":[123],"with":[125,153],"three":[126],"existing":[127],"models,":[128],"multilayer":[129],"perceptron":[130],"(MLP),":[131],"random":[132],"forest":[133],"(RF),":[134],"support":[136],"vector":[137],"machine":[138],"(SVM).":[139],"CNN-LSTM":[141],"model":[142],"achieves":[143],"highest":[145],"discrimination":[146],"accuracy":[147,157],"among":[148],"all":[149],"other":[151],"an":[154,161],"overall":[155],"test":[156],"99.3%":[159],"F1_score":[162],"0.98.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}