{"id":"https://openalex.org/W3108145079","doi":"https://doi.org/10.1109/icce-taiwan49838.2020.9258247","title":"Deep-Learning-Based Block Similarity Evaluation for Image Forensics","display_name":"Deep-Learning-Based Block Similarity Evaluation for Image Forensics","publication_year":2020,"publication_date":"2020-09-28","ids":{"openalex":"https://openalex.org/W3108145079","doi":"https://doi.org/10.1109/icce-taiwan49838.2020.9258247","mag":"3108145079"},"language":"en","primary_location":{"id":"doi:10.1109/icce-taiwan49838.2020.9258247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan49838.2020.9258247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","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/A5102784814","display_name":"Hsin\u2010Tzu Wang","orcid":"https://orcid.org/0000-0002-1138-5634"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hsin-Tzu Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5046617410","display_name":"Po-Chyi Su","orcid":"https://orcid.org/0000-0002-7457-8409"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Po-Chyi Su","raw_affiliation_strings":["Department of Computer Science and Information Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1709,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.4940772,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":1.0,"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":1.0,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9847999811172485,"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":0.9846000075340271,"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":0.8121321201324463},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7874085307121277},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.7553128004074097},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6770187616348267},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6404246091842651},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6349905729293823},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.569115161895752},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5647106766700745},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5304493308067322},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5128755569458008},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4453260004520416},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.43631428480148315},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4356245994567871}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8121321201324463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7874085307121277},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.7553128004074097},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6770187616348267},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6404246091842651},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6349905729293823},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.569115161895752},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5647106766700745},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5304493308067322},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5128755569458008},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4453260004520416},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.43631428480148315},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4356245994567871},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-taiwan49838.2020.9258247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan49838.2020.9258247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8267893555","display_name":null,"funder_award_id":"MOST106-2221-E-008-003-MY3,MOST108-2634-F-008-008","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1983586459","https://openalex.org/W2124351162","https://openalex.org/W2752015292","https://openalex.org/W2801560392","https://openalex.org/W2802701183"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W4291897433","https://openalex.org/W3011074480","https://openalex.org/W3192840557"],"abstract_inverted_index":{"Identifying":[0],"the":[1,29,56,82,89,111,115,120,152,172,193],"type":[2],"of":[3,55,58,68,91,122,146,154,174],"a":[4,13,38,65,98,140,164],"camera":[5,31,51,108],"used":[6,127],"to":[7,27,41,63,87,102,118,128,159,191],"capture":[8],"an":[9],"investigated":[10],"image":[11,15,46,59,123,156,185],"is":[12,126,180],"useful":[14],"forensic":[16,39],"tool,":[17],"which":[18],"usually":[19],"employs":[20],"machine":[21],"learning":[22,25],"or":[23],"deep":[24],"techniques":[26],"train":[28,97],"source":[30],"models.":[32,109],"In":[33],"this":[34,147],"research,":[35],"we":[36,133],"propose":[37],"scheme":[40,179],"detect":[42],"and":[43,169,187],"even":[44],"locate":[45,129],"manipulations":[47],"based":[48],"on":[49],"deep-learning-based":[50],"model":[52],"identification.":[53],"Because":[54],"diversity":[57],"tampering,":[60],"it's":[61],"difficult":[62],"collect":[64],"sufficient":[66],"amount":[67],"tampered":[69,79,130,137,175],"images":[70,80],"for":[71,106],"supervised":[72],"learning.":[73],"The":[74,144,177],"proposed":[75,178],"method":[76],"avoids":[77],"preparing":[78],"as":[81],"training":[83],"data":[84,190],"but":[85],"chooses":[86],"examine":[88],"information":[90],"original":[92],"pictures":[93],"only.":[94],"We":[95],"first":[96],"convolutional":[99],"neural":[100],"network":[101,117],"acquire":[103],"generic":[104],"features":[105],"identifying":[107],"Next,":[110],"similarity":[112],"measurement":[113],"using":[114],"Siamese":[116],"evaluate":[119],"consistency":[121,158],"block":[124,166],"pairs":[125],"areas.":[131],"Finally,":[132],"refine":[134],"more":[135],"accurate":[136],"areas":[138],"through":[139],"refined":[141],"segmentation":[142],"network.":[143],"contributions":[145],"research":[148],"include:":[149],"(1)":[150],"extending":[151],"study":[153],"determining":[155],"region":[157],"forensics":[160],"applications,":[161],"(2)":[162],"designing":[163],"better":[165],"comparison":[167],"algorithm,":[168],"(3)":[170],"improving":[171],"accuracy":[173],"regions.":[176],"tested":[181],"by":[182],"public-available":[183],"tempered":[184],"datasets":[186],"our":[188],"own":[189],"verify":[192],"feasibility.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
