{"id":"https://openalex.org/W3169872704","doi":"https://doi.org/10.1145/3447548.3467121","title":"Robust Object Detection Fusion Against Deception","display_name":"Robust Object Detection Fusion Against Deception","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3169872704","doi":"https://doi.org/10.1145/3447548.3467121","mag":"3169872704"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3467121","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-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/A5028240524","display_name":"Ka-Ho Chow","orcid":"https://orcid.org/0000-0001-5917-2577"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ka-Ho Chow","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100343991","display_name":"Ling Liu","orcid":"https://orcid.org/0000-0002-4138-3082"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ling Liu","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5028240524"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":1.2237,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.8307533,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2703","last_page":"2713"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12268","display_name":"Deception detection and forensic psychology","score":0.9779000282287598,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9528999924659729,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/robustness","display_name":"Robustness (evolution)","score":0.7497682571411133},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7497040033340454},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6489923000335693},{"id":"https://openalex.org/keywords/deception","display_name":"Deception","score":0.6478767395019531},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.6392459869384766},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5656701326370239},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.508241593837738},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5014498233795166},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.474975049495697},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4315699338912964},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4239279627799988},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34026551246643066},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09655994176864624}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7497682571411133},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7497040033340454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6489923000335693},{"id":"https://openalex.org/C2779267917","wikidata":"https://www.wikidata.org/wiki/Q170028","display_name":"Deception","level":2,"score":0.6478767395019531},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.6392459869384766},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5656701326370239},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.508241593837738},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5014498233795166},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.474975049495697},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4315699338912964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4239279627799988},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34026551246643066},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09655994176864624},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3447548.3467121","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:hub.hku.hk:10722/343518","is_oa":false,"landing_page_url":"https://hub.hku.hk/handle/10722/343518","pdf_url":null,"source":{"id":"https://openalex.org/S4377196271","display_name":"The HKU Scholars Hub (University of Hong Kong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I889458895","host_organization_name":"University of Hong Kong","host_organization_lineage":["https://openalex.org/I889458895"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference_Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G430006808","display_name":null,"funder_award_id":"2038029,2026945,1564097","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W2037227137","https://openalex.org/W2092961325","https://openalex.org/W2133665775","https://openalex.org/W2151572298","https://openalex.org/W2161969291","https://openalex.org/W2164598857","https://openalex.org/W2755542034","https://openalex.org/W2767075075","https://openalex.org/W2786977288","https://openalex.org/W2794557536","https://openalex.org/W2796347433","https://openalex.org/W2908113397","https://openalex.org/W2958435308","https://openalex.org/W2962748759","https://openalex.org/W2962765354","https://openalex.org/W2963207607","https://openalex.org/W2963726920","https://openalex.org/W2963967766","https://openalex.org/W2964110397","https://openalex.org/W2964121718","https://openalex.org/W2965198951","https://openalex.org/W2981495453","https://openalex.org/W3043144636","https://openalex.org/W3089073543","https://openalex.org/W3106250896"],"related_works":["https://openalex.org/W1971268144","https://openalex.org/W2154495931","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2353265673","https://openalex.org/W2031175860","https://openalex.org/W2152662039","https://openalex.org/W2726747157","https://openalex.org/W2010131506"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"network":[2],"(DNN)":[3],"based":[4],"object":[5,34],"detection":[6,49,79,90,131],"has":[7],"become":[8],"an":[9],"integral":[10],"part":[11],"of":[12,41,114,130,156],"numerous":[13],"cyber-physical":[14],"systems,":[15],"perceiving":[16],"physical":[17,157],"environments":[18],"and":[19,82,102],"responding":[20],"proactively":[21],"to":[22,87],"real-time":[23],"events.":[24],"Recent":[25],"studies":[26],"reveal":[27],"that":[28,139],"well-trained":[29],"multi-task":[30],"learners":[31],"like":[32],"DNN-based":[33],"detectors":[35,126],"perform":[36],"poorly":[37],"in":[38,144],"the":[39,146],"presence":[40],"deception.":[42],"This":[43],"paper":[44],"presents":[45],"FUSE,":[46],"a":[47,77,83,111,154],"deception-resilient":[48],"fusion":[50,60,72,80],"approach":[51],"with":[52],"three":[53,93,128],"novel":[54],"contributions.":[55],"First,":[56],"we":[57,75,109],"develop":[58],"diversity-enhanced":[59,64],"teaming":[61],"mechanisms,":[62],"including":[63,150],"joint":[65],"training":[66],"algorithms,":[67],"for":[68],"producing":[69],"high":[70],"diversity":[71],"detectors.":[73],"Second,":[74],"introduce":[76],"three-tier":[78],"framework":[81],"graph":[84],"partitioning":[85],"algorithm":[86],"construct":[88],"fusion-verified":[89],"outputs":[91],"through":[92],"mutually":[94],"reinforcing":[95],"components:":[96],"objectness":[97],"fusion,":[98,101],"bounding":[99],"box":[100],"classification":[103],"fusion.":[104],"Third":[105],"but":[106],"not":[107],"least,":[108],"provide":[110],"formal":[112],"analysis":[113],"robustness":[115,143],"enhancement":[116],"by":[117],"FUSE-protected":[118],"systems.":[119],"Extensive":[120],"experiments":[121],"are":[122],"conducted":[123],"on":[124,133],"eleven":[125],"from":[127],"families":[129],"algorithms":[132],"two":[134],"benchmark":[135],"datasets.":[136],"We":[137],"show":[138],"FUSE":[140],"guarantees":[141],"strong":[142],"mitigating":[145],"state-of-the-art":[147],"deception":[148],"attacks,":[149],"adversarial":[151],"patches":[152],"-":[153],"form":[155],"attacks":[158],"using":[159],"confined":[160],"visual":[161],"distortion.":[162]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
