{"id":"https://openalex.org/W4404030880","doi":"https://doi.org/10.1109/icccnt61001.2024.10724745","title":"Automated Road Extraction from Aerial Images: A Generative Approach with W-FuseNet Model","display_name":"Automated Road Extraction from Aerial Images: A Generative Approach with W-FuseNet Model","publication_year":2024,"publication_date":"2024-06-24","ids":{"openalex":"https://openalex.org/W4404030880","doi":"https://doi.org/10.1109/icccnt61001.2024.10724745"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt61001.2024.10724745","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt61001.2024.10724745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5000679712","display_name":"Debendra Muduli","orcid":"https://orcid.org/0000-0002-5697-3659"},"institutions":[{"id":"https://openalex.org/I4210125057","display_name":"Vivekananda Global University","ror":"https://ror.org/038mz4r36","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210125057"]},{"id":"https://openalex.org/I4387930198","display_name":"C.V. Raman Global University","ror":"https://ror.org/032583b91","country_code":null,"type":"education","lineage":["https://openalex.org/I4387930198"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Debendra Muduli","raw_affiliation_strings":["C.V. Raman Global University,Dept. Computer Science and Eng.,Bhubaneshwar,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"C.V. Raman Global University,Dept. Computer Science and Eng.,Bhubaneshwar,India","institution_ids":["https://openalex.org/I4210125057","https://openalex.org/I4387930198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101773623","display_name":"Santosh Kumar Sharma","orcid":"https://orcid.org/0000-0002-9912-9191"},"institutions":[{"id":"https://openalex.org/I4210125057","display_name":"Vivekananda Global University","ror":"https://ror.org/038mz4r36","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210125057"]},{"id":"https://openalex.org/I4387930198","display_name":"C.V. Raman Global University","ror":"https://ror.org/032583b91","country_code":null,"type":"education","lineage":["https://openalex.org/I4387930198"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Santosh Kumar Sharma","raw_affiliation_strings":["C.V. Raman Global University,Dept. Computer Science and Eng.,Bhubaneshwar,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"C.V. Raman Global University,Dept. Computer Science and Eng.,Bhubaneshwar,India","institution_ids":["https://openalex.org/I4210125057","https://openalex.org/I4387930198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079678778","display_name":"Debasish Pradhan","orcid":"https://orcid.org/0009-0000-4867-386X"},"institutions":[{"id":"https://openalex.org/I4210125057","display_name":"Vivekananda Global University","ror":"https://ror.org/038mz4r36","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210125057"]},{"id":"https://openalex.org/I4387930198","display_name":"C.V. Raman Global University","ror":"https://ror.org/032583b91","country_code":null,"type":"education","lineage":["https://openalex.org/I4387930198"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Debasish Pradhan","raw_affiliation_strings":["C.V. Raman Global University,Dept. Computer Science and Eng.,Bhubaneshwar,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"C.V. Raman Global University,Dept. Computer Science and Eng.,Bhubaneshwar,India","institution_ids":["https://openalex.org/I4210125057","https://openalex.org/I4387930198"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1102,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.76544292,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9980999827384949,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9832000136375427,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6230454444885254},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5963351130485535},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5782856345176697},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5248594284057617},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4528038799762726},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4293394088745117},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3734022378921509},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.36906325817108154},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.08639782667160034}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6230454444885254},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5963351130485535},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5782856345176697},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5248594284057617},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4528038799762726},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4293394088745117},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3734022378921509},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.36906325817108154},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.08639782667160034},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt61001.2024.10724745","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt61001.2024.10724745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","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":8,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2595964094","https://openalex.org/W2752782242","https://openalex.org/W2962978395","https://openalex.org/W3122458267","https://openalex.org/W3178773782","https://openalex.org/W4214496620","https://openalex.org/W4388713763"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W2601157893","https://openalex.org/W4395044357","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2373006798","https://openalex.org/W2087346071"],"abstract_inverted_index":{"This":[0],"research":[1],"introduces":[2],"an":[3,68],"automated":[4],"road":[5,117,140],"extraction":[6,141],"model":[7,61,142],"utilizing":[8],"deep":[9],"learning":[10,108],"techniques":[11],"for":[12,76,116],"high-resolution":[13],"aerial":[14],"imagery.":[15],"Focused":[16],"on":[17],"applications":[18],"in":[19],"urban":[20],"planning,":[21],"disaster":[22],"management,":[23],"and":[24,33,57,71,110,136,153],"logistics,":[25],"the":[26,81,84,101,111,122,144],"study":[27],"employs":[28],"convolutional":[29,113],"neural":[30],"networks":[31],"(CNNs)":[32],"a":[34,63,72],"conditional":[35],"Generative":[36],"Adversarial":[37],"Network":[38],"(cGAN)":[39],"architecture.":[40],"The":[41,59],"Massachusetts":[42,145],"Roads":[43,146],"Dataset,":[44],"comprising":[45],"1171":[46],"images,":[47],"is":[48,148],"subject":[49],"to":[50,89,128],"advanced":[51,154],"preprocessing":[52],"techniques,":[53],"including":[54],"resizing,":[55],"concatenation,":[56],"normalization.":[58],"proposed":[60],"features":[62],"carefully":[64],"crafted":[65],"generator":[66],"with":[67,132],"encoder-decoder":[69],"architecture":[70,152],"modified":[73],"Pix2pix-based":[74],"cGAN":[75],"semantic":[77],"segmentation.":[78],"Inspired":[79],"by":[80],"PatchGAN":[82],"concept,":[83],"discriminator":[85],"assesses":[86],"image":[87],"patches":[88],"distinguish":[90],"real":[91],"from":[92],"generated":[93],"images.":[94],"A":[95,138],"literature":[96],"survey":[97],"evaluates":[98],"methodologies,":[99],"emphasizing":[100],"Road":[102],"Structure":[103],"Refined":[104],"CNN":[105],"(RSRCNN),":[106],"generative":[107],"approaches,":[109],"fully":[112],"network":[114],"(FCN)":[115],"extraction.":[118],"Performance":[119],"analysis":[120],"demonstrates":[121],"model\u2019s":[123],"competitive":[124],"IoU":[125],"score":[126],"compared":[127],"existing":[129],"approaches":[130],"along":[131],"accuracy,":[133],"precision,":[134],"recall":[135],"f1-score.":[137],"novel":[139],"using":[143],"Dataset":[147],"introduced,":[149],"highlighting":[150],"WFuseNet":[151],"pre-processing":[155],"techniques.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
