{"id":"https://openalex.org/W2990544200","doi":"https://doi.org/10.1109/avss.2019.8909886","title":"Cosine Focal Loss-based Change Detection for Video Surveillance Systems","display_name":"Cosine Focal Loss-based Change Detection for Video Surveillance Systems","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2990544200","doi":"https://doi.org/10.1109/avss.2019.8909886","mag":"2990544200"},"language":"en","primary_location":{"id":"doi:10.1109/avss.2019.8909886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2019.8909886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","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/A5101032289","display_name":"Jae-Il Jung","orcid":null},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jae-Il Jung","raw_affiliation_strings":["Samsung Reserch, Samsung Electronics, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Samsung Reserch, Samsung Electronics, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044731253","display_name":"Junik Jang","orcid":null},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junik Jang","raw_affiliation_strings":["Samsung Reserch, Samsung Electronics, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Samsung Reserch, Samsung Electronics, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045599097","display_name":"Jonghee Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jonghee Hong","raw_affiliation_strings":["Samsung Reserch, Samsung Electronics, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Samsung Reserch, Samsung Electronics, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I2250650973"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101032289"],"corresponding_institution_ids":["https://openalex.org/I2250650973"],"apc_list":null,"apc_paid":null,"fwci":0.28,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6686355,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T12761","display_name":"Data Stream Mining Techniques","score":0.9970999956130981,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9929999709129333,"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/computer-science","display_name":"Computer science","score":0.7879775762557983},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6241465210914612},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47936588525772095},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.4694245457649231},{"id":"https://openalex.org/keywords/trigonometric-functions","display_name":"Trigonometric functions","score":0.46363896131515503},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.4591938257217407},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4520610570907593},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.43716001510620117},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3790225684642792},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.29159337282180786}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7879775762557983},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6241465210914612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47936588525772095},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.4694245457649231},{"id":"https://openalex.org/C178009071","wikidata":"https://www.wikidata.org/wiki/Q93344","display_name":"Trigonometric functions","level":2,"score":0.46363896131515503},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.4591938257217407},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4520610570907593},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.43716001510620117},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3790225684642792},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29159337282180786},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/avss.2019.8909886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2019.8909886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","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":31,"referenced_works":["https://openalex.org/W653074768","https://openalex.org/W1874745161","https://openalex.org/W1917901543","https://openalex.org/W1960877884","https://openalex.org/W2053724458","https://openalex.org/W2069057506","https://openalex.org/W2161381512","https://openalex.org/W2164720308","https://openalex.org/W2170140722","https://openalex.org/W2297432279","https://openalex.org/W2417256080","https://openalex.org/W2440599146","https://openalex.org/W2525668722","https://openalex.org/W2605856284","https://openalex.org/W2606629906","https://openalex.org/W2734349601","https://openalex.org/W2766141718","https://openalex.org/W2767019433","https://openalex.org/W2767094525","https://openalex.org/W2774176625","https://openalex.org/W2783946051","https://openalex.org/W2963351448","https://openalex.org/W2963516811","https://openalex.org/W2963846024","https://openalex.org/W3105220622","https://openalex.org/W4300179783","https://openalex.org/W6639338470","https://openalex.org/W6675675320","https://openalex.org/W6704278359","https://openalex.org/W6746777289","https://openalex.org/W6786050928"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W2376528221","https://openalex.org/W196800607","https://openalex.org/W2359428812","https://openalex.org/W3181296946","https://openalex.org/W2015705630","https://openalex.org/W2355368334","https://openalex.org/W2994927414"],"abstract_inverted_index":{"Change":[0],"detection":[1],"is":[2,67],"one":[3],"of":[4,14],"the":[5,52,64,94,100,110,114,118],"important":[6],"tasks":[7],"for":[8,61,73],"video":[9],"surveillance":[10],"systems.":[11],"A":[12],"variety":[13],"learning-based":[15],"approaches":[16],"have":[17],"been":[18],"proposed,":[19],"but":[20],"class":[21,49],"imbalance":[22],"in":[23,43,127],"training":[24],"data":[25],"degrades":[26],"their":[27],"learning":[28],"efficiency.":[29],"In":[30],"this":[31,48],"paper,":[32],"we":[33],"propose":[34],"a":[35,40,82,88],"cross":[36],"entropy":[37],"loss":[38,55,102,120],"with":[39,117],"modulating":[41],"term":[42],"cosine":[44],"form":[45],"to":[46,69,84],"handle":[47],"imbalance.":[50],"Although":[51],"original":[53],"focal":[54],"focuses":[56],"only":[57],"on":[58,92,106],"reducing":[59],"weights":[60],"well-classified":[62],"data,":[63],"proposed":[65,101,119],"function":[66],"designed":[68],"preserve":[70],"sufficient":[71],"gradients":[72],"rare":[74],"hard":[75],"samples":[76,91],"as":[77],"well.":[78],"This":[79],"property":[80],"allows":[81],"network":[83,95,115],"learn":[85],"mainly":[86],"from":[87],"few":[89],"significant":[90],"which":[93],"should":[96],"focus.":[97],"We":[98],"validate":[99],"through":[103],"various":[104,128],"experiments":[105],"CDNet2014":[107],"dataset,":[108],"and":[109],"results":[111],"show":[112],"that":[113],"trained":[116],"achieves":[121],"better":[122],"performance":[123],"than":[124],"other":[125],"state-of-the-arts":[126],"complex":[129],"scenarios.":[130]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}