{"id":"https://openalex.org/W2986165463","doi":"https://doi.org/10.3390/sym11111343","title":"Detection of Transcoding from H.264/AVC to HEVC Based on CU and PU Partition Types","display_name":"Detection of Transcoding from H.264/AVC to HEVC Based on CU and PU Partition Types","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W2986165463","doi":"https://doi.org/10.3390/sym11111343","mag":"2986165463"},"language":"en","primary_location":{"id":"doi:10.3390/sym11111343","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym11111343","pdf_url":"https://www.mdpi.com/2073-8994/11/11/1343/pdf?version=1572594309","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/11/11/1343/pdf?version=1572594309","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100422874","display_name":"Zhenzhen Zhang","orcid":"https://orcid.org/0000-0001-9776-8355"},"institutions":[{"id":"https://openalex.org/I4210135483","display_name":"Beijing Institute of Graphic Communication","ror":"https://ror.org/03yg3v757","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135483"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenzhen Zhang","raw_affiliation_strings":["School of Information Engineering, Beijing Institute of Graphic Communication, Beijing 102600, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Beijing Institute of Graphic Communication, Beijing 102600, China","institution_ids":["https://openalex.org/I4210135483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103201645","display_name":"Changbo Liu","orcid":"https://orcid.org/0000-0003-1403-1222"},"institutions":[{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]},{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changbo Liu","raw_affiliation_strings":["The Operation Center of Network Security Products China Telecom Corp. Ltd., Beijing 100010, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Operation Center of Network Security Products China Telecom Corp. Ltd., Beijing 100010, China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042040086","display_name":"Zhaohong Li","orcid":"https://orcid.org/0000-0001-6463-7666"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhaohong Li","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Information Security Technology, Guangzhou 510000, China","School of Electronic and Information Engineering, Beijing JiaoTong University, Beijing 100044, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Information Security Technology, Guangzhou 510000, China","institution_ids":[]},{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing JiaoTong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067543068","display_name":"Lifang Yu","orcid":"https://orcid.org/0000-0002-0508-7526"},"institutions":[{"id":"https://openalex.org/I4210135483","display_name":"Beijing Institute of Graphic Communication","ror":"https://ror.org/03yg3v757","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135483"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lifang Yu","raw_affiliation_strings":["School of Information Engineering, Beijing Institute of Graphic Communication, Beijing 102600, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Beijing Institute of Graphic Communication, Beijing 102600, China","institution_ids":["https://openalex.org/I4210135483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037494825","display_name":"Huanma Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huanma Yan","raw_affiliation_strings":["Jeejio Technology Co., Ltd, Beijing 100086, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jeejio Technology Co., Ltd, Beijing 100086, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5042040086"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.7144,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.75736997,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"11","issue":"11","first_page":"1343","last_page":"1343"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9998999834060669,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9998999834060669,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9994000196456909,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9972000122070312,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7990225553512573},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.6528980731964111},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5681114196777344},{"id":"https://openalex.org/keywords/transcoding","display_name":"Transcoding","score":0.5616332292556763},{"id":"https://openalex.org/keywords/coding-tree-unit","display_name":"Coding tree unit","score":0.48969653248786926},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4494360685348511},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4334806799888611},{"id":"https://openalex.org/keywords/algorithmic-efficiency","display_name":"Algorithmic efficiency","score":0.42990589141845703},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.352475106716156},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3243585228919983},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31280139088630676},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14181911945343018},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.14065015316009521},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09717020392417908}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7990225553512573},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6528980731964111},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5681114196777344},{"id":"https://openalex.org/C134535813","wikidata":"https://www.wikidata.org/wiki/Q1888734","display_name":"Transcoding","level":2,"score":0.5616332292556763},{"id":"https://openalex.org/C190750250","wikidata":"https://www.wikidata.org/wiki/Q13533439","display_name":"Coding tree unit","level":3,"score":0.48969653248786926},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4494360685348511},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4334806799888611},{"id":"https://openalex.org/C116709606","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Algorithmic efficiency","level":3,"score":0.42990589141845703},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.352475106716156},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3243585228919983},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31280139088630676},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14181911945343018},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.14065015316009521},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09717020392417908},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym11111343","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym11111343","pdf_url":"https://www.mdpi.com/2073-8994/11/11/1343/pdf?version=1572594309","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3729574bdbfe4fc2ab88e9400f411e1e","is_oa":true,"landing_page_url":"https://doaj.org/article/3729574bdbfe4fc2ab88e9400f411e1e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 11, Iss 11, p 1343 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/11/11/1343/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/sym11111343","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym11111343","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym11111343","pdf_url":"https://www.mdpi.com/2073-8994/11/11/1343/pdf?version=1572594309","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2670066982","display_name":null,"funder_award_id":"No. 61702034","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G691924587","display_name":null,"funder_award_id":"61702034","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7023509732","display_name":null,"funder_award_id":"2017B030314131","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320314997","display_name":"Strong","ror":"https://ror.org/041vyzr56"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2986165463.pdf","grobid_xml":"https://content.openalex.org/works/W2986165463.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W2029530782","https://openalex.org/W2051670588","https://openalex.org/W2076389153","https://openalex.org/W2153635508","https://openalex.org/W2329434622","https://openalex.org/W2412226701","https://openalex.org/W2547212236","https://openalex.org/W2563276378","https://openalex.org/W2737588607","https://openalex.org/W2753052222","https://openalex.org/W2807648315","https://openalex.org/W2892017671","https://openalex.org/W2895476614","https://openalex.org/W2908785750"],"related_works":["https://openalex.org/W3009161491","https://openalex.org/W2291137897","https://openalex.org/W2018760684","https://openalex.org/W2735437354","https://openalex.org/W1579233721","https://openalex.org/W4254232196","https://openalex.org/W2908833932","https://openalex.org/W2242376282","https://openalex.org/W2800164157","https://openalex.org/W2560965210"],"abstract_inverted_index":{"High":[0],"Efficiency":[1],"Video":[2],"Coding":[3],"(HEVC)":[4],"is":[5,42],"a":[6,75,112],"worldwide":[7],"popular":[8],"video":[9],"coding":[10,16,52],"standard":[11],"due":[12],"to":[13,23,32,44,111],"its":[14],"high":[15,132],"efficiency.":[17],"To":[18,34],"make":[19],"profits,":[20],"forgers":[21],"prefer":[22],"transcode":[24],"videos":[25,49,130],"from":[26],"previous":[27],"standards":[28],"such":[29,46],"as":[30,104],"H.264/AVC":[31],"HEVC.":[33],"deal":[35],"with":[36,131],"this":[37,80],"issue,":[38],"an":[39],"efficient":[40],"method":[41,125],"proposed":[43,124],"expose":[45],"transcoded":[47,128],"HEVC":[48,71,129],"based":[50],"on":[51],"unit":[53,57],"(CU)":[54],"and":[55,62,83,90,102,134,140],"prediction":[56],"(PU)":[58],"partition":[59,85],"types.":[60],"CU":[61,82],"PU":[63,84],"partitioning":[64],"are":[65,93,100,108],"two":[66],"unique":[67],"syntactic":[68],"units":[69],"of":[70,87,143],"that":[72,122],"can":[73,126],"reflect":[74],"video\u2019s":[76],"compression":[77],"history.":[78],"In":[79],"paper,":[81],"types":[86],"I":[88],"pictures":[89,92],"P":[91],"firstly":[94],"extracted.":[95],"Then,":[96],"their":[97],"mean":[98],"frequencies":[99],"calculated":[101],"concatenated":[103],"distinguishing":[105],"features,":[106],"which":[107],"further":[109],"sent":[110],"support":[113],"vector":[114],"machine":[115],"(SVM)":[116],"for":[117],"classification.":[118],"Experimental":[119],"results":[120],"show":[121],"the":[123],"identify":[127],"accuracy":[133],"has":[135],"strong":[136],"robustness":[137],"against":[138],"frame-deletion":[139],"shifted":[141],"Group":[142],"Pictures":[144],"(GOP)":[145],"structure":[146],"attacks.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}