{"id":"https://openalex.org/W4389474016","doi":"https://doi.org/10.1109/lsens.2023.3340562","title":"A Deforestation Detection Network Using Deep Learning-Based Semantic Segmentation","display_name":"A Deforestation Detection Network Using Deep Learning-Based Semantic Segmentation","publication_year":2023,"publication_date":"2023-12-08","ids":{"openalex":"https://openalex.org/W4389474016","doi":"https://doi.org/10.1109/lsens.2023.3340562"},"language":"en","primary_location":{"id":"doi:10.1109/lsens.2023.3340562","doi":"https://doi.org/10.1109/lsens.2023.3340562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsens.2023.3340562","pdf_url":null,"source":{"id":"https://openalex.org/S4210220808","display_name":"IEEE Sensors Letters","issn_l":"2475-1472","issn":["2475-1472"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","norway-1","poland-20","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Sensors Letters","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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":null,"display_name":"Pradeep Kumar Das","orcid":"https://orcid.org/0000-0002-3125-771X","observed_orcids":["https://orcid.org/0000-0002-3125-771X"]},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pradeep Kumar Das","raw_affiliation_strings":["School of Electronics Engineering, Vellore Institute of Technology Vellore, Vellore, India"],"raw_orcid":"https://orcid.org/0000-0002-3125-771X","affiliations":[{"raw_affiliation_string":"School of Electronics Engineering, Vellore Institute of Technology Vellore, Vellore, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058234884","display_name":"Adyasha Sahu","orcid":"https://orcid.org/0000-0003-0871-6962","observed_orcids":["https://orcid.org/0000-0003-0871-6962"]},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Adyasha Sahu","raw_affiliation_strings":["Department of Electronics and Communication Engineering, National Institute of Institute of Technology Rourkela, Rourkela, India"],"raw_orcid":"https://orcid.org/0000-0003-0871-6962","affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, National Institute of Institute of Technology Rourkela, Rourkela, India","institution_ids":["https://openalex.org/I16292982"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093446517","display_name":"Dias V. Xavy","orcid":"https://orcid.org/0009-0009-2680-8490","observed_orcids":["https://orcid.org/0009-0009-2680-8490"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dias V. Xavy","raw_affiliation_strings":["PharmaACE, Pune, India"],"raw_orcid":"https://orcid.org/0009-0009-2680-8490","affiliations":[{"raw_affiliation_string":"PharmaACE, Pune, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037663112","display_name":"Sukadev Meher","orcid":"https://orcid.org/0000-0003-4397-3139","observed_orcids":["https://orcid.org/0000-0003-4397-3139"]},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sukadev Meher","raw_affiliation_strings":["Department of Electronics and Communication Engineering, National Institute of Institute of Technology Rourkela, Rourkela, India"],"raw_orcid":"https://orcid.org/0000-0003-4397-3139","affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, National Institute of Institute of Technology Rourkela, Rourkela, India","institution_ids":["https://openalex.org/I16292982"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2345,"currency":"USD","value_usd":2345},"apc_paid":null,"fwci":1.4735,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.82174229,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"8","issue":"1","first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9413999915122986,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9413999915122986,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.05609999969601631,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"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/deforestation-detection","display_name":"deforestation detection","score":1.0},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"semantic segmentation","score":0.9039999842643738},{"id":"https://openalex.org/keywords/amazon-rainforest","display_name":"Amazon rainforest","score":0.8999999761581421},{"id":"https://openalex.org/keywords/segnet","display_name":"SegNet","score":0.8999999761581421},{"id":"https://openalex.org/keywords/resnet-18","display_name":"ResNet-18","score":0.8999999761581421},{"id":"https://openalex.org/keywords/shufflenet","display_name":"ShuffleNet","score":0.9990000128746033},{"id":"https://openalex.org/keywords/u-net","display_name":"U-Net","score":0.9610000252723694},{"id":"https://openalex.org/keywords/laplacian-of-gaussian","display_name":"Laplacian of Gaussian","score":0.7260000109672546},{"id":"https://openalex.org/keywords/image-deblurring","display_name":"image deblurring","score":0.8529999852180481},{"id":"https://openalex.org/keywords/edge-enhancement","display_name":"edge enhancement","score":0.9509999752044678},{"id":"https://openalex.org/keywords/image-denoising","display_name":"image denoising","score":0.8870000243186951},{"id":"https://openalex.org/keywords/computational-efficiency","display_name":"computational efficiency","score":0.6389999985694885}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6702266931533813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6355631351470947},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6036443710327148},{"id":"https://openalex.org/C2777399953","wikidata":"https://www.wikidata.org/wiki/Q2155658","display_name":"Deforestation (computer science)","level":2,"score":0.5868447422981262},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5472643971443176},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33245474100112915},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.05817520618438721}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsens.2023.3340562","doi":"https://doi.org/10.1109/lsens.2023.3340562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsens.2023.3340562","pdf_url":null,"source":{"id":"https://openalex.org/S4210220808","display_name":"IEEE Sensors Letters","issn_l":"2475-1472","issn":["2475-1472"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","norway-1","poland-20","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Sensors Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life on land","score":0.7605999708175659,"id":"https://metadata.un.org/sdg/15"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1910657905","https://openalex.org/W2194775991","https://openalex.org/W2395611524","https://openalex.org/W2592939477","https://openalex.org/W2892300883","https://openalex.org/W2963125010","https://openalex.org/W2964309882","https://openalex.org/W2986617423","https://openalex.org/W3011156941","https://openalex.org/W3021436325","https://openalex.org/W3137244318","https://openalex.org/W3170241800","https://openalex.org/W4205687832","https://openalex.org/W4210403414","https://openalex.org/W4285257508","https://openalex.org/W4289656111","https://openalex.org/W4307217876","https://openalex.org/W4307844358","https://openalex.org/W4328007689","https://openalex.org/W4386197239","https://openalex.org/W4386301343","https://openalex.org/W4388505256","https://openalex.org/W4393575498"],"related_works":["https://openalex.org/W4296743007","https://openalex.org/W3080079534","https://openalex.org/W4200302434","https://openalex.org/W3011156941","https://openalex.org/W4205687832","https://openalex.org/W4405179619","https://openalex.org/W7218234697","https://openalex.org/W7119289423","https://openalex.org/W7214963740","https://openalex.org/W4389737449"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1,90,98,140],"is":[2,14,18,48,67,100,184],"an":[3,60,95],"important":[4],"task":[5],"in":[6,72,129],"which":[7,161],"the":[8,55,73,88,104,121,143,166,170,198],"class":[9],"label":[10],"of":[11,106,123,135],"each":[12],"pixel":[13],"predicted.":[15],"Thus,":[16,142],"it":[17,36,47],"quite":[19],"tough":[20],"compared":[21],"with":[22],"classification":[23],"and":[24,43,113,138,158,169,173,190],"classical":[25],"segmentation.":[26,119],"Recently,":[27],"deforestation":[28,52,71],"has":[29],"been":[30],"a":[31,177],"serious":[32],"environmental":[33,39],"issue,":[34],"as":[35,150],"causes":[37],"numerous":[38],"concerns:":[40],"climate":[41],"change":[42],"ecological":[44],"loss.":[45],"Hence,":[46],"essential":[49],"to":[50,53,69,86,115,133],"recognize":[51],"save":[54],"environment.":[56],"In":[57,175],"this":[58],"work,":[59],"efficient":[61,96,172],"convolution":[62],"neural":[63],"network":[64,171],"(CNN)":[65],"model":[66],"proposed":[68,101,144,199],"identify":[70],"Amazon":[74],"Rainforest":[75],"more":[76,91,117],"precisely.":[77],"At":[78],"first,":[79],"two":[80],"modified":[81,108,111,130,179],"SegNet":[82,131],"methods":[83],"are":[84,162],"presented":[85],"make":[87],"semantic":[89,97,139],"effective.":[92],"More":[93],"importantly,":[94],"framework":[99,145,200],"by":[102],"integrating":[103],"merits":[105],"ResNet18-based":[107],"SegNet,":[109,112],"ShuffleNet-based":[110],"UNet":[114],"yield":[116],"effective":[118],"Moreover,":[120],"employment":[122],"computationally":[124],"faster":[125],"ResNet18":[126],"or":[127],"ShuffleNet":[128],"leads":[132],"improvement":[134],"computational":[136],"efficiency":[137],"performance.":[141],"also":[146,195],"retains":[147],"advantages":[148],"such":[149],"residual":[151],"learning,":[152],"skip":[153],"connection,":[154],"pointwise":[155],"group":[156],"convolution,":[157],"channel":[159],"shuffling,":[160],"responsible":[163],"for":[164,186],"making":[165],"optimization":[167],"easier":[168],"faster.":[174],"addition,":[176],"Laplacian-of-Gaussian-based":[178],"high":[180],"boosting":[181],"filter":[182],"(LoGMHF)":[183],"employed":[185],"deblurring,":[187],"edge":[188],"enhancement,":[189],"denoising.":[191],"The":[192],"experimental":[193],"analysis":[194],"shows":[196],"that":[197],"outperforms":[201],"others.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":6}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2023-12-09T00:00:00"}