{"id":"https://openalex.org/W4322743913","doi":"https://doi.org/10.3390/rs15051384","title":"A Depth-Wise Separable U-Net Architecture with Multiscale Filters to Detect Sinkholes","display_name":"A Depth-Wise Separable U-Net Architecture with Multiscale Filters to Detect Sinkholes","publication_year":2023,"publication_date":"2023-02-28","ids":{"openalex":"https://openalex.org/W4322743913","doi":"https://doi.org/10.3390/rs15051384"},"language":"en","primary_location":{"id":"doi:10.3390/rs15051384","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15051384","pdf_url":"https://www.mdpi.com/2072-4292/15/5/1384/pdf?version=1677808584","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/2072-4292/15/5/1384/pdf?version=1677808584","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078030620","display_name":"Rasha Alshawi","orcid":null},"institutions":[{"id":"https://openalex.org/I192396691","display_name":"University of New Orleans","ror":"https://ror.org/034mtvk83","country_code":"US","type":"education","lineage":["https://openalex.org/I192396691","https://openalex.org/I2799628689"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rasha Alshawi","raw_affiliation_strings":["Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA","institution_ids":["https://openalex.org/I192396691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055092646","display_name":"Md Tamjidul Hoque","orcid":"https://orcid.org/0000-0002-0110-2194"},"institutions":[{"id":"https://openalex.org/I192396691","display_name":"University of New Orleans","ror":"https://ror.org/034mtvk83","country_code":"US","type":"education","lineage":["https://openalex.org/I192396691","https://openalex.org/I2799628689"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Md Tamjidul Hoque","raw_affiliation_strings":["Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA","institution_ids":["https://openalex.org/I192396691"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014487135","display_name":"Maik C. Flanagin","orcid":null},"institutions":[{"id":"https://openalex.org/I1306490931","display_name":"United States Army Corps of Engineers","ror":"https://ror.org/05w4e8v21","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1306490931","https://openalex.org/I1330347796"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maik C. Flanagin","raw_affiliation_strings":["US Army Corps of Engineers, New Orleans, LA 70118, USA"],"affiliations":[{"raw_affiliation_string":"US Army Corps of Engineers, New Orleans, LA 70118, USA","institution_ids":["https://openalex.org/I1306490931"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5055092646"],"corresponding_institution_ids":["https://openalex.org/I192396691"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":3.9614,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.93738383,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"15","issue":"5","first_page":"1384","last_page":"1384"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12083","display_name":"Karst Systems and Hydrogeology","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/1904","display_name":"Earth-Surface Processes"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12083","display_name":"Karst Systems and Hydrogeology","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/1904","display_name":"Earth-Surface Processes"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11787","display_name":"Oral and Maxillofacial Pathology","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.972000002861023,"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/computer-science","display_name":"Computer science","score":0.7485537528991699},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6786550283432007},{"id":"https://openalex.org/keywords/sinkhole","display_name":"Sinkhole","score":0.626273512840271},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6137175559997559},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6114658117294312},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6082761883735657},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5299749374389648},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5040447115898132},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5026960372924805},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4831692576408386},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.4795531928539276},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.45705389976501465},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.41503986716270447},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35802552103996277},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1554126739501953},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11591887474060059},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.08683964610099792}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7485537528991699},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6786550283432007},{"id":"https://openalex.org/C49223487","wikidata":"https://www.wikidata.org/wiki/Q188734","display_name":"Sinkhole","level":3,"score":0.626273512840271},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6137175559997559},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6114658117294312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6082761883735657},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5299749374389648},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5040447115898132},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5026960372924805},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4831692576408386},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.4795531928539276},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.45705389976501465},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.41503986716270447},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35802552103996277},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1554126739501953},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11591887474060059},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.08683964610099792},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C182348080","wikidata":"https://www.wikidata.org/wiki/Q16817","display_name":"Karst","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15051384","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15051384","pdf_url":"https://www.mdpi.com/2072-4292/15/5/1384/pdf?version=1677808584","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:c375722c7f5d455a96256357ebff3238","is_oa":true,"landing_page_url":"https://doaj.org/article/c375722c7f5d455a96256357ebff3238","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 5, p 1384 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/5/1384/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15051384","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","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15051384","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15051384","pdf_url":"https://www.mdpi.com/2072-4292/15/5/1384/pdf?version=1677808584","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":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4322743913.pdf"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W109260593","https://openalex.org/W1901129140","https://openalex.org/W2069318476","https://openalex.org/W2097117768","https://openalex.org/W2143915663","https://openalex.org/W2792005857","https://openalex.org/W2963666905","https://openalex.org/W2980998394","https://openalex.org/W2983181739","https://openalex.org/W3012456963","https://openalex.org/W4210583964","https://openalex.org/W4281557545","https://openalex.org/W4312305429","https://openalex.org/W4313229413","https://openalex.org/W4319068710","https://openalex.org/W6807527814","https://openalex.org/W6849659142"],"related_works":["https://openalex.org/W2552485568","https://openalex.org/W2043656548","https://openalex.org/W2002122708","https://openalex.org/W125799629","https://openalex.org/W3022213123","https://openalex.org/W4229766761","https://openalex.org/W2034363770","https://openalex.org/W2908627775","https://openalex.org/W2810330923","https://openalex.org/W4289763776"],"abstract_inverted_index":{"Numerous":[0],"variants":[1],"of":[2,26,55,60,68,79,108,151],"the":[3,50,66,72,77,88,95,122,128,135,157,160,184,197],"basic":[4],"deep":[5,116],"segmentation":[6,132],"model\u2014U-Net\u2014have":[7],"emerged":[8],"in":[9],"recent":[10],"years,":[11],"achieving":[12,147],"reliable":[13],"performance":[14,30],"across":[15],"different":[16,56],"benchmarks.":[17],"In":[18],"this":[19],"paper,":[20],"we":[21,112],"propose":[22,113],"an":[23,148,190],"improved":[24],"version":[25],"U-Net":[27],"with":[28,46,163],"higher":[29],"and":[31,87,103,144,153,159,165,179,192],"reduced":[32,172],"complexity.":[33],"This":[34],"improvement":[35,150,195],"was":[36],"achieved":[37,177],"by":[38],"introducing":[39],"a":[40,105,114,171],"sparsely":[41],"connected":[42],"depth-wise":[43,61],"separable":[44,62],"block":[45,124],"multiscale":[47],"filters,":[48],"enabling":[49],"network":[51,119],"to":[52,93,125],"capture":[53],"features":[54],"scales.":[57],"The":[58],"use":[59],"convolution":[63],"significantly":[64],"reduces":[65],"number":[67],"trainable":[69],"parameters,":[70],"making":[71],"training":[73,173],"faster,":[74],"while":[75],"reducing":[76],"risk":[78],"overfitting.":[80],"We":[81],"used":[82],"our":[83],"developed":[84],"sinkhole":[85,129,158],"dataset":[86,92],"available":[89],"benchmark":[90],"nuclei":[91,161],"assess":[94],"proposed":[96,123],"model\u2019s":[97],"performance.":[98],"Pixel-wise":[99],"annotation":[100],"is":[101,189],"laborious":[102],"requires":[104],"great":[106],"deal":[107],"human":[109],"expertise;":[110],"therefore,":[111],"fully":[115],"convolutional":[117],"autoencoder":[118],"that":[120],"utilizes":[121],"automatically":[126],"annotate":[127],"dataset.":[130],"Our":[131],"model":[133],"outperformed":[134],"state-of-the-art":[136],"methods,":[137],"including":[138],"U-Net,":[139,141,143,146],"Attention":[140],"Depth-Separable":[142],"Inception":[145],"average":[149,194],"1.2%":[152],"1.4%,":[154],"respectively,":[155,187],"on":[156,183],"datasets,":[162,186],"94%":[164],"92%":[166],"accuracy,":[167],"as":[168,170],"well":[169],"time.":[174],"It":[175],"also":[176],"83%":[178],"80%":[180],"intersection-over-union":[181],"(IoU)":[182],"two":[185],"which":[188],"11.8%":[191],"9.3%":[193],"over":[196],"above-mentioned":[198],"models.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}