{"id":"https://openalex.org/W3080829100","doi":"https://doi.org/10.1145/3404555.3404579","title":"Intrusion Detection of Abnormal Objects for Railway Scenes Using Infrared Images","display_name":"Intrusion Detection of Abnormal Objects for Railway Scenes Using Infrared Images","publication_year":2020,"publication_date":"2020-04-23","ids":{"openalex":"https://openalex.org/W3080829100","doi":"https://doi.org/10.1145/3404555.3404579","mag":"3080829100"},"language":"en","primary_location":{"id":"doi:10.1145/3404555.3404579","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3404555.3404579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence","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/A5100701079","display_name":"Yi Liu","orcid":"https://orcid.org/0000-0003-3086-7273"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Liu","raw_affiliation_strings":["School of Information Science and Technology, North China University of Technology China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, North China University of Technology China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071835685","display_name":"Dong Han","orcid":"https://orcid.org/0000-0002-0692-6467"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Dong","raw_affiliation_strings":["School of Information Science and Technology, North China University of Technology China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, North China University of Technology China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101736058","display_name":"Yundong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yundong Li","raw_affiliation_strings":["School of Information Science and Technology, North China University of Technology China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, North China University of Technology China","institution_ids":["https://openalex.org/I1456306"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1456306"],"apc_list":null,"apc_paid":null,"fwci":0.0854,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.32461418,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"269","last_page":"274"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9961000084877014,"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"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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":0.6332007646560669},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6229544878005981},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.5502682328224182},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5258006453514099},{"id":"https://openalex.org/keywords/intrusion","display_name":"Intrusion","score":0.49384742975234985},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.44721320271492004},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4180935323238373},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2740900218486786},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.23745694756507874},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.06012088060379028},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0572352409362793}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6332007646560669},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6229544878005981},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.5502682328224182},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5258006453514099},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.49384742975234985},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.44721320271492004},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4180935323238373},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2740900218486786},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.23745694756507874},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.06012088060379028},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0572352409362793},{"id":"https://openalex.org/C17409809","wikidata":"https://www.wikidata.org/wiki/Q161764","display_name":"Geochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3404555.3404579","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3404555.3404579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2104984687","https://openalex.org/W2109255472","https://openalex.org/W2134939446","https://openalex.org/W2173520492","https://openalex.org/W2193145675","https://openalex.org/W2807869636","https://openalex.org/W2962793481","https://openalex.org/W2963037989","https://openalex.org/W3106250896","https://openalex.org/W3121413330"],"related_works":["https://openalex.org/W2357468538","https://openalex.org/W1577110157","https://openalex.org/W2355007334","https://openalex.org/W2906422846","https://openalex.org/W2390009783","https://openalex.org/W4254602698","https://openalex.org/W2394461323","https://openalex.org/W2349441905","https://openalex.org/W2361044160","https://openalex.org/W2133389611"],"abstract_inverted_index":{"Intrusion":[0],"detection":[1,30,37,95,132],"of":[2,15,49],"abnormal":[3,35,113],"objects":[4,114],"is":[5,97,109,137],"critical":[6],"to":[7,54,111],"avoid":[8],"traffic":[9],"accidents":[10],"and":[11,85,129],"ensure":[12],"the":[13,34,72,100,105,124,130],"safety":[14],"train":[16],"operations.":[17],"Computer-vision":[18],"based":[19],"approaches":[20],"using":[21,38,69,99],"RGB":[22],"images":[23,40,51,74,82,88,117],"have":[24],"been":[25],"intensively":[26],"investigated":[27],"for":[28,115,134],"intrusion":[29],"at":[31,41,83,89,118],"daytime.":[32],"However,":[33],"object":[36,94,131],"infrared":[39,50,116],"nighttime":[42,135],"remains":[43],"more":[44],"challenging":[45],"because":[46],"training":[47],"samples":[48],"are":[52,75],"limited":[53],"address":[55],"this":[56],"issue,":[57],"we":[58],"propose":[59],"a":[60,92],"data":[61,126],"augmentation":[62,127],"strategy":[63,128],"motivated":[64],"by":[65],"image":[66],"style":[67],"transfer":[68],"CycleGAN.":[70],"First,":[71],"synthetic":[73,102],"generated":[76,101],"which":[77],"conditioned":[78],"on":[79],"railway":[80],"scene":[81,87,136],"daytime":[84],"non-railway":[86],"nighttime.":[90,119],"Then,":[91],"SSD":[93,107],"model":[96,108],"trained":[98,106],"samples.":[103],"Finally,":[104],"used":[110],"detect":[112],"Experimental":[120],"results":[121],"demonstrate":[122],"that":[123],"proposed":[125],"method":[133],"effective.":[138]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}