{"id":"https://openalex.org/W4386212652","doi":"https://doi.org/10.1109/siu59756.2023.10223740","title":"Enhancing Object Detection Algorithms by Synthetic Aerial Images","display_name":"Enhancing Object Detection Algorithms by Synthetic Aerial Images","publication_year":2023,"publication_date":"2023-07-05","ids":{"openalex":"https://openalex.org/W4386212652","doi":"https://doi.org/10.1109/siu59756.2023.10223740"},"language":"en","primary_location":{"id":"doi:10.1109/siu59756.2023.10223740","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/siu59756.2023.10223740","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st Signal Processing and Communications Applications Conference (SIU)","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/A5061693983","display_name":"Can Y\u0131lmaz","orcid":"https://orcid.org/0000-0002-5994-508X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Can YILMAZ","raw_affiliation_strings":["Bah&#x00E7;e&#x015F;ehir &#x00DC;niversitesi, Yapay Zeka M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bah&#x00E7;e&#x015F;ehir &#x00DC;niversitesi, Yapay Zeka M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084553294","display_name":"Bahri MARA\u015e","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bahri MARA\u015e","raw_affiliation_strings":["Bogazi&#x00E7;i &#x00DC;niversitesi, Elektrik ve Elektronik M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bogazi&#x00E7;i &#x00DC;niversitesi, Elektrik ve Elektronik M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101597872","display_name":"G\u00f6rkem Y\u0131lmaz","orcid":"https://orcid.org/0000-0003-2189-5854"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G\u00f6rkem YILMAZ","raw_affiliation_strings":["Bah&#x00E7;e&#x015F;ehir &#x00DC;niversitesi, Bilgisayar M&#x00FC;hendisligi B&#x00F6;l&#x00FC;m&#x00FC;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bah&#x00E7;e&#x015F;ehir &#x00DC;niversitesi, Bilgisayar M&#x00FC;hendisligi B&#x00F6;l&#x00FC;m&#x00FC;","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111938507","display_name":"G\u00f6ksu CEYLAN","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G\u00f6ksu CEYLAN","raw_affiliation_strings":["Bah&#x00E7;e&#x015F;ehir &#x00DC;niversitesi, Yapay Zeka M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bah&#x00E7;e&#x015F;ehir &#x00DC;niversitesi, Yapay Zeka M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092705793","display_name":"\u00d6nder HAMAMCIO\u011eLU","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u00d6nder HAMAMCIO\u011eLU","raw_affiliation_strings":["Bah&#x00E7;e&#x015F;ehir &#x00DC;niversitesi, Bilgisayar M&#x00FC;hendisligi B&#x00F6;l&#x00FC;m&#x00FC;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bah&#x00E7;e&#x015F;ehir &#x00DC;niversitesi, Bilgisayar M&#x00FC;hendisligi B&#x00F6;l&#x00FC;m&#x00FC;","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075089107","display_name":"Nafiz Ar\u0131ca","orcid":"https://orcid.org/0000-0002-3810-5866"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nafiz ARICA","raw_affiliation_strings":["Piri Reis &#x00DC;niversitesi, Bili&#x015F;im Sistemleri M&#x00FC;hendisligi B&#x00F6;l&#x00FC;m&#x00FC;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Piri Reis &#x00DC;niversitesi, Bili&#x015F;im Sistemleri M&#x00FC;hendisligi B&#x00F6;l&#x00FC;m&#x00FC;","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088978453","display_name":"A. Ert\u00fcz\u00fcn","orcid":"https://orcid.org/0000-0002-7674-3738"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ay\u015f\u0131n Baytan ERT\u00dcZ\u00dcN","raw_affiliation_strings":["Bogazi&#x00E7;i &#x00DC;niversitesi, Elektrik ve Elektronik M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bogazi&#x00E7;i &#x00DC;niversitesi, Elektrik ve Elektronik M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9945999979972839,"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":0.9945999979972839,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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":0.762088418006897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7398905158042908},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7098824977874756},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6584489941596985},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6573687195777893},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6503384113311768},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5615769028663635},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5512422919273376},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5403945446014404},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.5375582575798035},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.49893689155578613},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.44590675830841064},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4250656068325043},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.4249439537525177},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.4107581377029419},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.31997597217559814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.762088418006897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7398905158042908},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7098824977874756},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6584489941596985},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6573687195777893},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6503384113311768},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5615769028663635},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5512422919273376},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5403945446014404},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.5375582575798035},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.49893689155578613},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.44590675830841064},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4250656068325043},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.4249439537525177},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.4107581377029419},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31997597217559814}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu59756.2023.10223740","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/siu59756.2023.10223740","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4000000059604645,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W2901421464","https://openalex.org/W3036286480","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W4287027631","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582"],"abstract_inverted_index":{"In":[0,79],"order":[1],"to":[2,44,54],"accurately":[3],"perform":[4],"object":[5,100,112],"detection":[6,101,107,113],"by":[7],"deep":[8],"convolutional":[9],"neural":[10],"networks":[11],"(DCNN)":[12],"in":[13,76,91],"videos,":[14],"ob\u00adtained":[15],"from":[16,62],"unmanned":[17],"aerial":[18,83,121,125],"vehicles":[19],"(UAVs),":[20],"many":[21],"example":[22],"images":[23,84,126],"of":[24,50,57,106,109,119],"objects":[25],"containing":[26,67],"annotations":[27],"such":[28],"as":[29],"ground":[30,70],"truth":[31],"class":[32],"information,":[33],"bounding":[34],"box,":[35],"optical":[36],"flow,":[37],"occlusion":[38],"and":[39,52,98],"segmentation":[40],"are":[41],"required.":[42],"Due":[43],"the":[45,55,58,77,117,131],"difficulties":[46],"faced":[47],"during":[48,130],"annotation":[49,87],"scenarios,":[51],"due":[53],"inadequacy":[56],"scenario":[59],"diversity":[60],"resulting":[61],"environmental":[63],"conditions,":[64],"a":[65],"dataset":[66],"above":[68],"mentioned":[69],"truths":[71],"has":[72],"not":[73],"been":[74],"found":[75],"literature.":[78],"this":[80],"study,":[81],"synthetic":[82,120],"with":[85,116],"various":[86],"information":[88],"were":[89],"created":[90],"different":[92],"scenarios":[93],"while":[94],"composing":[95],"virtual":[96],"worlds,":[97],"enhancing":[99],"algorithms":[102],"is":[103],"aimed.":[104],"Enhancement":[105],"results":[108],"DCNN":[110],"based":[111],"algorithms,":[114],"trained":[115],"support":[118],"images,":[122],"on":[123],"real-world":[124],"significantly,":[127],"was":[128],"observed":[129],"experiments,":[132],"conducted.":[133]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
