{"id":"https://openalex.org/W4382009029","doi":"https://doi.org/10.3390/rs15092412","title":"Improvements in Forest Segmentation Accuracy Using a New Deep Learning Architecture and Data Augmentation Technique","display_name":"Improvements in Forest Segmentation Accuracy Using a New Deep Learning Architecture and Data Augmentation Technique","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4382009029","doi":"https://doi.org/10.3390/rs15092412"},"language":"en","primary_location":{"id":"doi:10.3390/rs15092412","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15092412","pdf_url":"https://www.mdpi.com/2072-4292/15/9/2412/pdf?version=1683265051","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/9/2412/pdf?version=1683265051","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101216907","display_name":"Yan He","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan He","raw_affiliation_strings":["Beijing Laboratory of Advanced Information Network, Beijing 100021, China","Faculty of Information Technology, Beijing University of Technology, Beijing 100021, China"],"affiliations":[{"raw_affiliation_string":"Beijing Laboratory of Advanced Information Network, Beijing 100021, China","institution_ids":[]},{"raw_affiliation_string":"Faculty of Information Technology, Beijing University of Technology, Beijing 100021, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008153237","display_name":"Kebin Jia","orcid":"https://orcid.org/0000-0001-7620-2221"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kebin Jia","raw_affiliation_strings":["Beijing Laboratory of Advanced Information Network, Beijing 100021, China","Faculty of Information Technology, Beijing University of Technology, Beijing 100021, China"],"affiliations":[{"raw_affiliation_string":"Beijing Laboratory of Advanced Information Network, Beijing 100021, China","institution_ids":[]},{"raw_affiliation_string":"Faculty of Information Technology, Beijing University of Technology, Beijing 100021, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043504429","display_name":"Zhihao Wei","orcid":"https://orcid.org/0000-0002-1607-2725"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihao Wei","raw_affiliation_strings":["School of Earth and Space Sciences, Peking University, Beijing 100871, China"],"affiliations":[{"raw_affiliation_string":"School of Earth and Space Sciences, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008153237"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.5064,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.79898575,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"15","issue":"9","first_page":"2412","last_page":"2412"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9988999962806702,"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":0.9936000108718872,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7881557941436768},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6518439054489136},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6394515633583069},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6382651925086975},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5660756826400757},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.549362301826477},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5029701590538025},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4430605173110962},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"Satellite imagery","score":0.44203075766563416},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4266052544116974},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39081090688705444},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3434978723526001},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.09271955490112305},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08360186219215393}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7881557941436768},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6518439054489136},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6394515633583069},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6382651925086975},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5660756826400757},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.549362301826477},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5029701590538025},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4430605173110962},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.44203075766563416},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4266052544116974},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39081090688705444},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3434978723526001},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.09271955490112305},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08360186219215393},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15092412","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15092412","pdf_url":"https://www.mdpi.com/2072-4292/15/9/2412/pdf?version=1683265051","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:24bd24cd50f841f9be0183d8e734ba38","is_oa":true,"landing_page_url":"https://doaj.org/article/24bd24cd50f841f9be0183d8e734ba38","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 9, p 2412 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/9/2412/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15092412","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 15; Issue 9; Pages: 2412","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15092412","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15092412","pdf_url":"https://www.mdpi.com/2072-4292/15/9/2412/pdf?version=1683265051","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4382009029.pdf"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W1665214252","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2022224360","https://openalex.org/W2042055195","https://openalex.org/W2155906534","https://openalex.org/W2261059368","https://openalex.org/W2560023338","https://openalex.org/W2761605926","https://openalex.org/W2776146695","https://openalex.org/W2904702542","https://openalex.org/W2911709005","https://openalex.org/W2921499963","https://openalex.org/W2923165032","https://openalex.org/W2928133111","https://openalex.org/W2935706473","https://openalex.org/W2940726923","https://openalex.org/W2944976011","https://openalex.org/W2954996726","https://openalex.org/W2955058313","https://openalex.org/W2955477134","https://openalex.org/W2963881378","https://openalex.org/W2964309882","https://openalex.org/W2974283536","https://openalex.org/W2979970650","https://openalex.org/W3014120959","https://openalex.org/W3014368515","https://openalex.org/W3017026587","https://openalex.org/W3021074965","https://openalex.org/W3042861622","https://openalex.org/W3045553371","https://openalex.org/W3047553761","https://openalex.org/W3049577063","https://openalex.org/W3084798277","https://openalex.org/W3088162569","https://openalex.org/W3111358813","https://openalex.org/W3113835931","https://openalex.org/W3117652191","https://openalex.org/W3117977576","https://openalex.org/W3118804988","https://openalex.org/W3126400685","https://openalex.org/W3127036765","https://openalex.org/W3153820698","https://openalex.org/W3174822832","https://openalex.org/W3183653952","https://openalex.org/W3185840992","https://openalex.org/W3198800506","https://openalex.org/W4205319818","https://openalex.org/W4206691754","https://openalex.org/W4210489441","https://openalex.org/W4280558447","https://openalex.org/W4285594764","https://openalex.org/W4289731689","https://openalex.org/W4294118512","https://openalex.org/W4312339267","https://openalex.org/W4361011318","https://openalex.org/W4362639281","https://openalex.org/W4366991553","https://openalex.org/W6631190155","https://openalex.org/W6745143564","https://openalex.org/W6765492952","https://openalex.org/W6800908015"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Forests":[0],"are":[1],"critical":[2],"to":[3,76,126,133],"mitigating":[4],"global":[5,16],"climate":[6,10],"change":[7],"and":[8,18,68,138,207],"regulating":[9],"through":[11],"their":[12],"role":[13],"in":[14,41],"the":[15,47,86,97,111,116,128,131,139,143,171,195],"carbon":[17],"water":[19],"cycles.":[20],"Accurate":[21],"monitoring":[22],"of":[23,49,61,88,99,119,130,146,183],"forest":[24,89,120,153,174],"cover":[25],"is,":[26],"therefore,":[27],"essential.":[28],"Image":[29],"segmentation":[30,73,91,157,189],"networks":[31,36,55,74],"based":[32,163],"on":[33,164],"convolutional":[34],"neural":[35],"have":[37],"shown":[38],"significant":[39],"advantages":[40],"remote":[42,121,154,202],"sensing":[43,122,155,203],"image":[44,72,90,156,188],"analysis":[45],"with":[46],"development":[48],"deep":[50,53],"learning.":[51],"However,":[52],"learning":[54],"typically":[56],"require":[57],"a":[58,93,105,151],"large":[59],"amount":[60],"manual":[62,100],"ground":[63],"truth":[64],"labels":[65],"for":[66],"training,":[67],"existing":[69],"widely":[70],"used":[71],"struggle":[75],"extract":[77,134,199],"details":[78],"from":[79,142,201],"large-scale":[80],"high":[81],"resolution":[82],"satellite":[83,147],"imagery.":[84],"Improving":[85],"accuracy":[87],"remains":[92],"challenge.":[94],"To":[95],"reduce":[96],"cost":[98],"labelling,":[101],"this":[102],"paper":[103],"proposed":[104,150,196],"data":[106,113],"augmentation":[107],"method":[108,179],"that":[109,177,194],"expands":[110],"training":[112],"by":[114,159],"modifying":[115],"spatial":[117],"distribution":[118],"images.":[123],"In":[124],"addition,":[125],"improve":[127],"ability":[129],"network":[132,158],"multi-scale":[135,161],"detailed":[136],"features":[137,162],"feature":[140],"information":[141],"NIR":[144],"band":[145],"images,":[148],"we":[149],"high-resolution":[152],"fusing":[160],"double":[165],"input.":[166],"The":[167],"experimental":[168],"results":[169,192],"using":[170],"Sanjiangyuan":[172],"plateau":[173],"dataset":[175],"show":[176],"our":[178],"achieves":[180],"an":[181],"IoU":[182],"90.19%,":[184],"which":[185],"outperforms":[186],"prevalent":[187],"networks.":[190],"These":[191],"demonstrate":[193],"approaches":[197],"can":[198],"forests":[200],"images":[204],"more":[205],"effectively":[206],"accurately.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3}],"updated_date":"2026-02-28T09:26:25.869077","created_date":"2025-10-10T00:00:00"}