{"id":"https://openalex.org/W4407937556","doi":"https://doi.org/10.1109/tits.2025.3542411","title":"A Deep Learning Image Segmentation Model for Detection of Weak Vehicle-Generated Quasi-Static Strain in Distributed Acoustic Sensing","display_name":"A Deep Learning Image Segmentation Model for Detection of Weak Vehicle-Generated Quasi-Static Strain in Distributed Acoustic Sensing","publication_year":2025,"publication_date":"2025-02-25","ids":{"openalex":"https://openalex.org/W4407937556","doi":"https://doi.org/10.1109/tits.2025.3542411"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2025.3542411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3542411","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","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/A5101625904","display_name":"Fei Peng","orcid":"https://orcid.org/0000-0002-8323-3234"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Peng","raw_affiliation_strings":["College of Electrical Engineering, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-8323-3234","affiliations":[{"raw_affiliation_string":"College of Electrical Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084643975","display_name":"Ziyang Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyang Zhu","raw_affiliation_strings":["College of Electrical Engineering, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412278","display_name":"Yujie Zhang","orcid":"https://orcid.org/0000-0002-4375-0149"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujie Zhang","raw_affiliation_strings":["College of Electrical Engineering, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-4375-0149","affiliations":[{"raw_affiliation_string":"College of Electrical Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101754601","display_name":"Qiang Miao","orcid":"https://orcid.org/0000-0002-8879-7266"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Miao","raw_affiliation_strings":["College of Electrical Engineering, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-8879-7266","affiliations":[{"raw_affiliation_string":"College of Electrical Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":7.9784,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.98176265,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"26","issue":"6","first_page":"8933","last_page":"8944"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9210000038146973,"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"}},"topics":[{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9210000038146973,"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":0.5400633811950684},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5206053256988525},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5015888214111328},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4932045340538025},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4903697967529297},{"id":"https://openalex.org/keywords/distributed-acoustic-sensing","display_name":"Distributed acoustic sensing","score":0.44255369901657104},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4296983480453491},{"id":"https://openalex.org/keywords/strain","display_name":"Strain (injury)","score":0.4177754819393158},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11269694566726685},{"id":"https://openalex.org/keywords/optical-fiber","display_name":"Optical fiber","score":0.09232890605926514},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.07131439447402954}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5400633811950684},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5206053256988525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5015888214111328},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4932045340538025},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4903697967529297},{"id":"https://openalex.org/C158543913","wikidata":"https://www.wikidata.org/wiki/Q5283133","display_name":"Distributed acoustic sensing","level":4,"score":0.44255369901657104},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4296983480453491},{"id":"https://openalex.org/C2778022156","wikidata":"https://www.wikidata.org/wiki/Q576145","display_name":"Strain (injury)","level":2,"score":0.4177754819393158},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11269694566726685},{"id":"https://openalex.org/C194232370","wikidata":"https://www.wikidata.org/wiki/Q162","display_name":"Optical fiber","level":2,"score":0.09232890605926514},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.07131439447402954},{"id":"https://openalex.org/C21651689","wikidata":"https://www.wikidata.org/wiki/Q1397427","display_name":"Fiber optic sensor","level":3,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2025.3542411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3542411","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4300000071525574}],"awards":[{"id":"https://openalex.org/G1661629573","display_name":null,"funder_award_id":"62303335","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3299167625","display_name":null,"funder_award_id":"23NSFSC3797","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3815619227","display_name":null,"funder_award_id":"52075349","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6408212812","display_name":null,"funder_award_id":"YJ201654","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8189763053","display_name":null,"funder_award_id":"2022M712234","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2889769843","https://openalex.org/W2890715669","https://openalex.org/W2965560845","https://openalex.org/W2968734351","https://openalex.org/W2979901318","https://openalex.org/W2997018269","https://openalex.org/W3036586801","https://openalex.org/W3114918704","https://openalex.org/W3151929627","https://openalex.org/W3209685110","https://openalex.org/W3211326549","https://openalex.org/W4214826366","https://openalex.org/W4289550194","https://openalex.org/W4292975530","https://openalex.org/W4294982636","https://openalex.org/W4295949689","https://openalex.org/W4296209895","https://openalex.org/W4312326591","https://openalex.org/W4312655715","https://openalex.org/W4324381471","https://openalex.org/W4380318196","https://openalex.org/W4382461142","https://openalex.org/W4387546409","https://openalex.org/W4388102558","https://openalex.org/W4395033748","https://openalex.org/W6874386491"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2731899572","https://openalex.org/W2900734788","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W2910997950","https://openalex.org/W2029741436","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Distributed":[0],"Acoustic":[1],"Sensing":[2],"(DAS)":[3],"instrument":[4],"connected":[5],"to":[6,133,182],"dark":[7],"fibers":[8],"that":[9,87,172],"widely":[10],"deployed":[11],"near":[12],"roads":[13],"can":[14],"collect":[15],"quasi-static":[16,95,123,165],"strain":[17,96],"signals":[18,124,137,166],"generated":[19,97],"by":[20,98,106],"vehicles":[21,86,100],"over":[22],"a":[23,45,127,139,143,151],"large":[24,140],"range.":[25],"This":[26],"approach":[27],"addresses":[28],"the":[29,67,91,118],"high":[30,176],"deployment":[31,74],"and":[32,35,75,103,109,125,179],"maintenance":[33,76],"costs":[34],"limited":[36],"coverage":[37],"of":[38,120],"traditional":[39],"roadside":[40],"sensing":[41,64,69],"technologies,":[42],"making":[43],"DAS":[44,68,110,183],"highly":[46],"promising":[47],"vehicle":[48,122,164],"detection":[49],"technology":[50],"for":[51,82,147],"intelligent":[52],"transportation":[53],"systems.":[54],"However,":[55],"using":[56,138,167],"existing":[57],"communication":[58],"cables":[59,65],"rather":[60],"than":[61],"specially":[62],"laid":[63],"as":[66],"medium,":[70],"while":[71],"offering":[72],"ultra-low":[73],"cost":[77],"advantages,":[78],"poses":[79],"significant":[80],"challenges":[81],"detecting":[83],"lightweight,":[84],"low-speed":[85,159],"are":[88,101],"far":[89],"from":[90],"fiber":[92],"cable.":[93],"The":[94,169],"such":[99],"low":[102],"easily":[104],"overwhelmed":[105],"environmental":[107],"noise":[108],"fading":[111,184],"noise.":[112,185],"In":[113,150],"this":[114],"paper,":[115],"we":[116,161],"analyze":[117],"causes":[119],"weak":[121,136],"propose":[126],"Unet":[128],"image":[129],"segmentation":[130],"network,":[131],"trained":[132],"recognize":[134],"these":[135],"window":[141],"with":[142],"small":[144],"step":[145],"size":[146],"data":[148],"input.":[149],"typical":[152],"campus":[153],"test":[154],"scenario":[155],"containing":[156],"numerous":[157],"lightweight":[158],"vehicles,":[160],"tested":[162],"various":[163],"Unet.":[168],"results":[170],"demonstrated":[171],"our":[173],"method":[174],"has":[175],"recognition":[177],"accuracy":[178],"excellent":[180],"resistance":[181]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":8}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}