{"id":"https://openalex.org/W3002027913","doi":"https://doi.org/10.1109/icce-berlin47944.2019.8966136","title":"Utilization of the open source datasets for semantic segmentation in automotive vision","display_name":"Utilization of the open source datasets for semantic segmentation in automotive vision","publication_year":2019,"publication_date":"2019-09-08","ids":{"openalex":"https://openalex.org/W3002027913","doi":"https://doi.org/10.1109/icce-berlin47944.2019.8966136","mag":"3002027913"},"language":"en","primary_location":{"id":"doi:10.1109/icce-berlin47944.2019.8966136","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-berlin47944.2019.8966136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 9th International Conference on Consumer Electronics (ICCE-Berlin)","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/A5044758821","display_name":"Du\u0161an Kenji\u0107","orcid":"https://orcid.org/0000-0002-7873-0789"},"institutions":[{"id":"https://openalex.org/I2801863878","display_name":"RT-RK Institute for Computer Based Systems (Serbia)","ror":"https://ror.org/02vm8jd66","country_code":"RS","type":"company","lineage":["https://openalex.org/I2801863878"]}],"countries":["RS"],"is_corresponding":true,"raw_author_name":"Dusan Kenjic","raw_affiliation_strings":["Based Systems,RT-RK Institute for Computer,Novi Sad,Serbia","RT-RK Institute for Computer, Based Systems, Novi Sad, Serbia"],"affiliations":[{"raw_affiliation_string":"Based Systems,RT-RK Institute for Computer,Novi Sad,Serbia","institution_ids":["https://openalex.org/I2801863878"]},{"raw_affiliation_string":"RT-RK Institute for Computer, Based Systems, Novi Sad, Serbia","institution_ids":["https://openalex.org/I2801863878"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075678208","display_name":"Filip Baba","orcid":null},"institutions":[{"id":"https://openalex.org/I2801863878","display_name":"RT-RK Institute for Computer Based Systems (Serbia)","ror":"https://ror.org/02vm8jd66","country_code":"RS","type":"company","lineage":["https://openalex.org/I2801863878"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Filip Baba","raw_affiliation_strings":["Based Systems,RT-RK Institute for Computer,Novi Sad,Serbia","RT-RK Institute for Computer, Based Systems, Novi Sad, Serbia"],"affiliations":[{"raw_affiliation_string":"Based Systems,RT-RK Institute for Computer,Novi Sad,Serbia","institution_ids":["https://openalex.org/I2801863878"]},{"raw_affiliation_string":"RT-RK Institute for Computer, Based Systems, Novi Sad, Serbia","institution_ids":["https://openalex.org/I2801863878"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063816223","display_name":"Dragan Samard\u017eija","orcid":"https://orcid.org/0000-0002-1763-6991"},"institutions":[{"id":"https://openalex.org/I170726198","display_name":"University of Novi Sad","ror":"https://ror.org/00xa57a59","country_code":"RS","type":"education","lineage":["https://openalex.org/I170726198"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Dragan Samardzija","raw_affiliation_strings":["University of Novi Sad,Novi Sad,Serbia","University of Novi Sad, Novi Sad, Serbia"],"affiliations":[{"raw_affiliation_string":"University of Novi Sad,Novi Sad,Serbia","institution_ids":["https://openalex.org/I170726198"]},{"raw_affiliation_string":"University of Novi Sad, Novi Sad, Serbia","institution_ids":["https://openalex.org/I170726198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039397955","display_name":"Zvonimir Kaprocki","orcid":null},"institutions":[{"id":"https://openalex.org/I2801863878","display_name":"RT-RK Institute for Computer Based Systems (Serbia)","ror":"https://ror.org/02vm8jd66","country_code":"RS","type":"company","lineage":["https://openalex.org/I2801863878"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Zvonimir Kaprocki","raw_affiliation_strings":["Based Systems,RT-RK Institute for Computer,Novi Sad,Serbia","RT-RK Institute for Computer, Based Systems, Novi Sad, Serbia"],"affiliations":[{"raw_affiliation_string":"Based Systems,RT-RK Institute for Computer,Novi Sad,Serbia","institution_ids":["https://openalex.org/I2801863878"]},{"raw_affiliation_string":"RT-RK Institute for Computer, Based Systems, Novi Sad, Serbia","institution_ids":["https://openalex.org/I2801863878"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5044758821"],"corresponding_institution_ids":["https://openalex.org/I2801863878"],"apc_list":null,"apc_paid":null,"fwci":0.2024,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.56327072,"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":"420","last_page":"423"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9939000010490417,"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":0.8426282405853271},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.681961178779602},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6640862226486206},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6388739943504333},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6164484024047852},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.60682612657547},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5661829710006714},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5659960508346558},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4662927985191345},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4382162392139435},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43186402320861816},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36330291628837585}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8426282405853271},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.681961178779602},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6640862226486206},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6388739943504333},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6164484024047852},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.60682612657547},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5661829710006714},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5659960508346558},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4662927985191345},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4382162392139435},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43186402320861816},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36330291628837585},{"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},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-berlin47944.2019.8966136","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-berlin47944.2019.8966136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 9th International Conference on Consumer Electronics (ICCE-Berlin)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1598681710","https://openalex.org/W2062385571","https://openalex.org/W2076063813","https://openalex.org/W2102605133","https://openalex.org/W2159668971","https://openalex.org/W2340897893","https://openalex.org/W2579912550","https://openalex.org/W2792152757","https://openalex.org/W2966975099","https://openalex.org/W3040318838","https://openalex.org/W4300124531","https://openalex.org/W6635939161","https://openalex.org/W6669567237","https://openalex.org/W6675026286","https://openalex.org/W6732355326","https://openalex.org/W6737309142","https://openalex.org/W6748755788"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W4231274751","https://openalex.org/W1549363203","https://openalex.org/W2154063878","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W1538046993","https://openalex.org/W4239293476","https://openalex.org/W1566995892"],"abstract_inverted_index":{"Great":[0],"advancements":[1],"in":[2,39],"deep-learning-based":[3],"machine":[4],"vision":[5],"are":[6,32],"boosting":[7],"the":[8,42,104,133,140],"automotive":[9],"industry":[10],"potential":[11],"to":[12,34,60,94,102,139],"accurately":[13],"recognize":[14],"vehicle":[15],"environment.":[16],"The":[17],"need":[18],"for":[19,48,127],"high":[20],"quality":[21],"datasets":[22,47,67,101],"is":[23],"of":[24,41,58,82,92,116,142],"critical":[25],"importance":[26],"when":[27,137],"training":[28,119],"neural":[29],"networks":[30],"which":[31],"used":[33,53],"detect":[35],"and":[36,79,96,118],"classify":[37],"objects":[38],"front":[40],"vehicle.":[43],"Available":[44],"open":[45,99,145],"source":[46,100,146],"semantic":[49],"segmentation":[50],"can":[51],"be":[52],"by":[54],"a":[55,90],"wide":[56],"community":[57],"researchers":[59],"develop":[61],"next":[62],"generation":[63],"self-driving":[64],"functions.":[65],"Those":[66,107],"have":[68],"severe":[69],"limitations":[70],"such":[71],"as":[72,121,123],"class":[73],"imbalance,":[74],"unobserved":[75],"objects,":[76],"erroneous":[77],"labelling":[78],"limited":[80],"number":[81],"covered":[83],"scenarios.":[84],"In":[85],"this":[86],"paper,":[87],"we":[88],"propose":[89],"sequence":[91],"steps":[93,108],"combine":[95],"manipulate":[97],"existing":[98],"maximize":[103],"inference":[105,135],"performance.":[106],"include":[109],"relabeling":[110],"with":[111],"outlier":[112],"removal,":[113],"class-driven":[114],"balancing":[115],"validation":[117],"datasets,":[120],"well":[122],"targeted":[124],"image":[125],"manipulation":[126],"scarce":[128],"classes.":[129],"Our":[130],"evaluation":[131],"indicates":[132],"improved":[134],"accuracy":[136],"compared":[138],"usage":[141],"most":[143],"common":[144],"datasets.":[147]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
