{"id":"https://openalex.org/W4200046206","doi":"https://doi.org/10.1145/3487075.3487184","title":"An Improved Faster R-CNN for Railway Fastening System Detection","display_name":"An Improved Faster R-CNN for Railway Fastening System Detection","publication_year":2021,"publication_date":"2021-10-19","ids":{"openalex":"https://openalex.org/W4200046206","doi":"https://doi.org/10.1145/3487075.3487184"},"language":"en","primary_location":{"id":"doi:10.1145/3487075.3487184","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487075.3487184","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","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/A5079745626","display_name":"Xinfeng Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinfeng Peng","raw_affiliation_strings":["School of Automation, Southeast University, China and Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, China and Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, China","institution_ids":["https://openalex.org/I1327237609","https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shuzhen Tong","orcid":null},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuzhen Tong","raw_affiliation_strings":["School of Automation, Southeast University, China and Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, China and Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, China","institution_ids":["https://openalex.org/I1327237609","https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066658319","display_name":"Xiaobo Lu","orcid":"https://orcid.org/0000-0002-7707-7538"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobo Lu","raw_affiliation_strings":["School of Automation, Southeast University, China and Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, China and Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, China","institution_ids":["https://openalex.org/I1327237609","https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104019323","display_name":"Yun Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I2801441622","display_name":"China Railway Corporation","ror":"https://ror.org/044wv3489","country_code":"CN","type":"government","lineage":["https://openalex.org/I2801441622","https://openalex.org/I4210122102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Wei","raw_affiliation_strings":["Beijing Mass Transit Railway Operation Corporation Limited, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Mass Transit Railway Operation Corporation Limited, China","institution_ids":["https://openalex.org/I2801441622"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7074,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.69329621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9983999729156494,"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":0.9983999729156494,"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"}},{"id":"https://openalex.org/T10842","display_name":"Railway Engineering and Dynamics","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9488999843597412,"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":0.772581934928894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7053858041763306},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5987886190414429},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5669199824333191},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.504819929599762},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49883365631103516},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49778056144714355},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.49501198530197144},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4653860628604889},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45622357726097107},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.43703263998031616},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.42969390749931335},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.4185831844806671},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.41173532605171204}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.772581934928894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7053858041763306},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5987886190414429},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5669199824333191},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.504819929599762},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49883365631103516},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49778056144714355},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.49501198530197144},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4653860628604889},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45622357726097107},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.43703263998031616},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42969390749931335},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.4185831844806671},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.41173532605171204},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3487075.3487184","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487075.3487184","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","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":15,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W2194775991","https://openalex.org/W2406523001","https://openalex.org/W2565639579","https://openalex.org/W2752825721","https://openalex.org/W2772386856","https://openalex.org/W2884585870","https://openalex.org/W2912130719","https://openalex.org/W2914732806","https://openalex.org/W2964444661","https://openalex.org/W2964479623","https://openalex.org/W2985228975","https://openalex.org/W3049770295","https://openalex.org/W3092600573","https://openalex.org/W3153249728"],"related_works":["https://openalex.org/W2105642232","https://openalex.org/W3197833032","https://openalex.org/W4386081464","https://openalex.org/W3207332793","https://openalex.org/W2499612753","https://openalex.org/W3113278055","https://openalex.org/W2750709484","https://openalex.org/W4296474495","https://openalex.org/W3139036545","https://openalex.org/W2994927414"],"abstract_inverted_index":{"In":[0],"the":[1,22,36,39,52,77,104,109,114,128,136],"automatic":[2],"railway":[3],"anomaly":[4],"inspection":[5],"technology":[6],"based":[7],"on":[8,80],"image":[9,98],"processing":[10],"and":[11,89,95,131,134],"deep":[12],"learning,":[13],"an":[14],"effective":[15],"algorithm":[16],"used":[17,56,86],"for":[18,61,93],"high-precision":[19],"detection":[20,130,133],"of":[21,38,47,113,138],"fastening":[23],"system":[24],"is":[25,33,42],"very":[26],"important,":[27],"especially":[28],"in":[29,117],"turnout":[30,40],"sections.":[31],"It":[32],"challenging":[34],"because":[35],"background":[37],"sections":[41],"complicated":[43],"with":[44,103],"various":[45],"types":[46],"targets.":[48,63],"This":[49],"paper":[50,85,119],"improved":[51,115,135],"Faster":[53,106],"R-CNN":[54,107],"model,":[55,108],"multi-scale":[57],"feature":[58],"map":[59],"fusion":[60],"small":[62],"And":[64],"modified":[65],"predefined":[66],"anchor":[67],"to":[68,75,123],"generate":[69],"region":[70],"proposals,":[71],"added":[72],"attention":[73],"module":[74],"make":[76],"network":[78],"focus":[79],"meaningful":[81],"feature.":[82],"Besides,":[83],"this":[84,118],"cross-entropy":[87],"function":[88,92],"SmoothL1":[90],"loss":[91],"training":[94],"labeled":[96],"1200":[97],"samples":[99],"as":[100],"dataset.":[101],"Compared":[102],"original":[105],"experimental":[110],"results":[111],"(AP)":[112],"model":[116],"increased":[120],"from":[121],"96.3%":[122],"98.9%,":[124],"which":[125],"effectively":[126],"reduced":[127],"fault":[129],"missed":[132],"accuracy":[137],"location.":[139]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
