{"id":"https://openalex.org/W4303980418","doi":"https://doi.org/10.3390/s22197477","title":"Research on Ground Object Classification Method of High Resolution Remote-Sensing Images Based on Improved DeeplabV3+","display_name":"Research on Ground Object Classification Method of High Resolution Remote-Sensing Images Based on Improved DeeplabV3+","publication_year":2022,"publication_date":"2022-10-02","ids":{"openalex":"https://openalex.org/W4303980418","doi":"https://doi.org/10.3390/s22197477","pmid":"https://pubmed.ncbi.nlm.nih.gov/36236574"},"language":"en","primary_location":{"id":"doi:10.3390/s22197477","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22197477","pdf_url":"https://www.mdpi.com/1424-8220/22/19/7477/pdf?version=1665451941","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/19/7477/pdf?version=1665451941","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015001687","display_name":"Junjie Fu","orcid":"https://orcid.org/0000-0002-4702-2392"},"institutions":[{"id":"https://openalex.org/I1284762954","display_name":"Zhejiang A & F University","ror":"https://ror.org/02vj4rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I1284762954"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Fu","raw_affiliation_strings":["College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China","institution_ids":["https://openalex.org/I1284762954"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068465357","display_name":"Xiaomei Yi","orcid":"https://orcid.org/0000-0001-5846-7461"},"institutions":[{"id":"https://openalex.org/I1284762954","display_name":"Zhejiang A & F University","ror":"https://ror.org/02vj4rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I1284762954"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaomei Yi","raw_affiliation_strings":["College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China","Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province, Hangzhou 311300, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China","institution_ids":["https://openalex.org/I1284762954"]},{"raw_affiliation_string":"Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province, Hangzhou 311300, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109408929","display_name":"Guoying Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I1284762954","display_name":"Zhejiang A & F University","ror":"https://ror.org/02vj4rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I1284762954"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoying Wang","raw_affiliation_strings":["College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China","Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province, Hangzhou 311300, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China","institution_ids":["https://openalex.org/I1284762954"]},{"raw_affiliation_string":"Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province, Hangzhou 311300, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112493750","display_name":"Lufeng Mo","orcid":null},"institutions":[{"id":"https://openalex.org/I1284762954","display_name":"Zhejiang A & F University","ror":"https://ror.org/02vj4rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I1284762954"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lufeng Mo","raw_affiliation_strings":["College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China","Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province, Hangzhou 311300, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China","institution_ids":["https://openalex.org/I1284762954"]},{"raw_affiliation_string":"Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province, Hangzhou 311300, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006744731","display_name":"Peng Wu","orcid":"https://orcid.org/0000-0001-8946-3447"},"institutions":[{"id":"https://openalex.org/I1284762954","display_name":"Zhejiang A & F University","ror":"https://ror.org/02vj4rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I1284762954"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Wu","raw_affiliation_strings":["College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China","Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province, Hangzhou 311300, China"],"raw_orcid":"https://orcid.org/0000-0001-8946-3447","affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China","institution_ids":["https://openalex.org/I1284762954"]},{"raw_affiliation_string":"Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province, Hangzhou 311300, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052342306","display_name":"Kasanda Ernest Kapula","orcid":null},"institutions":[{"id":"https://openalex.org/I1284762954","display_name":"Zhejiang A & F University","ror":"https://ror.org/02vj4rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I1284762954"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kasanda Ernest Kapula","raw_affiliation_strings":["College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer Science, Zhejiang A and F University, Hangzhou 311300, China","institution_ids":["https://openalex.org/I1284762954"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5068465357"],"corresponding_institution_ids":["https://openalex.org/I1284762954"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":1.9904,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.85068574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"22","issue":"19","first_page":"7477","last_page":"7477"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9948999881744385,"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":0.9948999881744385,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9855999946594238,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9800999760627747,"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":0.6945432424545288},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.666565477848053},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5623753070831299},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49163681268692017},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.4824596047401428},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45575326681137085},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4538189470767975},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45252081751823425},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.44191431999206543},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41883665323257446},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.41366034746170044},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41102084517478943},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3895036578178406},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1124802827835083},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08956238627433777}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6945432424545288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.666565477848053},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5623753070831299},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49163681268692017},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.4824596047401428},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45575326681137085},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4538189470767975},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45252081751823425},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.44191431999206543},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41883665323257446},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.41366034746170044},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41102084517478943},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3895036578178406},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1124802827835083},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08956238627433777},{"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":[{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D058998","descriptor_name":"Remote Sensing Technology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D058998","descriptor_name":"Remote Sensing Technology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D058998","descriptor_name":"Remote Sensing Technology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22197477","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22197477","pdf_url":"https://www.mdpi.com/1424-8220/22/19/7477/pdf?version=1665451941","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},{"id":"pmid:36236574","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36236574","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:70a5a57e9f524cff86f7830f577f79fb","is_oa":true,"landing_page_url":"https://doaj.org/article/70a5a57e9f524cff86f7830f577f79fb","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 22, Iss 19, p 7477 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/19/7477/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22197477","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":"Sensors; Volume 22; Issue 19; Pages: 7477","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9571339","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9571339","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22197477","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22197477","pdf_url":"https://www.mdpi.com/1424-8220/22/19/7477/pdf?version=1665451941","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4303980418.pdf","grobid_xml":"https://content.openalex.org/works/W4303980418.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2395611524","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2630837129","https://openalex.org/W2787091153","https://openalex.org/W2787659442","https://openalex.org/W2802942478","https://openalex.org/W2803728921","https://openalex.org/W2809544832","https://openalex.org/W2866634454","https://openalex.org/W2906622835","https://openalex.org/W2941529264","https://openalex.org/W2963163009","https://openalex.org/W2963481014","https://openalex.org/W2967731069","https://openalex.org/W2981719849","https://openalex.org/W3014060899","https://openalex.org/W3017971322","https://openalex.org/W3091811842","https://openalex.org/W3104610662","https://openalex.org/W3108705364","https://openalex.org/W3109301572","https://openalex.org/W3113272803","https://openalex.org/W3119776735","https://openalex.org/W3129042754","https://openalex.org/W3132455321","https://openalex.org/W3134831088","https://openalex.org/W3177052299","https://openalex.org/W3192504607","https://openalex.org/W4200274794","https://openalex.org/W4206479630","https://openalex.org/W4207073624","https://openalex.org/W6790679990","https://openalex.org/W6996559486"],"related_works":["https://openalex.org/W2522537526","https://openalex.org/W4308659218","https://openalex.org/W2998228095","https://openalex.org/W2791535170","https://openalex.org/W2001271057","https://openalex.org/W2468641972","https://openalex.org/W2894651257","https://openalex.org/W3200590620","https://openalex.org/W4200172193","https://openalex.org/W4303926741"],"abstract_inverted_index":{"Ground-object":[0],"classification":[1],"using":[2],"remote-sensing":[3,31,48,79,165],"images":[4,69,80],"of":[5,36,77,85,93,144,172],"high":[6,71],"resolution":[7],"is":[8,54,64,81,88,96,179,195,198],"widely":[9],"used":[10,66,109],"in":[11,29],"land":[12],"planning,":[13],"ecological":[14],"monitoring,":[15],"and":[16,90,115,125,155,188,206,212],"resource":[17],"protection.":[18],"Traditional":[19],"image":[20,49,148,166],"segmentation":[21,75,160],"technology":[22],"has":[23,136],"poor":[24],"effect":[25],"on":[26,60,163,176,191],"complex":[27],"scenes":[28],"high-resolution":[30,47,78,164],"images.":[32],"In":[33],"the":[34,74,83,91,102,111,122,126,137,142,170,173,189],"field":[35],"deep":[37,40,56],"learning,":[38],"some":[39],"neural":[41,57],"networks":[42],"are":[43],"being":[44],"applied":[45],"to":[46,67,129,146],"segmentation.":[50],"The":[51],"DeeplabV3+":[52,103,185,203],"network":[53,58,86,95,107,145,152,186,204],"a":[55],"based":[59],"encoder-decoder":[61],"architecture,":[62],"which":[63],"commonly":[65],"segment":[68],"with":[70],"precision.":[72],"However,":[73],"accuracy":[76],"poor,":[82],"number":[84],"parameters":[87],"large,":[89],"cost":[92],"training":[94,153],"high.":[97],"Therefore,":[98],"this":[99],"paper":[100],"improves":[101],"network.":[104],"Firstly,":[105],"MobileNetV2":[106],"was":[108,119],"as":[110],"backbone":[112],"feature-extraction":[113,123],"network,":[114],"an":[116],"attention-mechanism":[117],"module":[118,124,128],"added":[120],"after":[121],"ASPP":[127],"introduce":[130],"focal":[131],"loss":[132],"balance.":[133],"Our":[134],"design":[135],"following":[138],"advantages:":[139],"it":[140,150,156],"enhances":[141],"ability":[143],"extract":[147],"features;":[149],"reduces":[151],"costs;":[154],"achieves":[157],"better":[158],"semantic":[159],"accuracy.":[161],"Experiments":[162],"datasets":[167,178,194],"show":[168],"that":[169],"mIou":[171,190,205],"proposed":[174],"method":[175],"WHDLD":[177],"64.76%,":[180],"4.24%":[181],"higher":[182,200],"than":[183,201],"traditional":[184,202,208],"mIou,":[187],"CCF":[192],"BDCI":[193],"64.58%.":[196],"This":[197],"5.35%":[199],"outperforms":[207],"DeeplabV3+,":[209],"U-NET,":[210],"PSP-NET":[211],"MACU-net":[213],"networks.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}