乐胖代购免代理版

{"id":"https://openalex.org/W4229079333","doi":"https://doi.org/10.1080/01969722.2022.2071408","title":"Integration of Deep Learned and Handcrafted Features for Image Retargeting Quality Assessment","display_name":"Integration of Deep Learned and Handcrafted Features for Image Retargeting Quality Assessment","publication_year":2022,"publication_date":"2022-05-05","ids":{"openalex":"https://openalex.org/W4229079333","doi":"https://doi.org/10.1080/01969722.2022.2071408"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1080/01969722.2022.2071408","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5030464340","display_name":"Ahmad Absetan","orcid":"https://orcid.org/0000-0002-3293-4313"},"institutions":[{"id":"https://openalex.org/I1187138","display_name":"Razi University","ror":"https://ror.org/02ynb0474","country_code":"IR","type":"funder","lineage":["https://openalex.org/I1187138"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Ahmad Absetan","raw_affiliation_strings":["Department of Computer Engineering and Information Technology, Razi University, Kermanshah, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering and Information Technology, Razi University, Kermanshah, Iran","institution_ids":["https://openalex.org/I1187138"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057450178","display_name":"Abdolhossein Fathi","orcid":"https://orcid.org/0000-0003-0387-5518"},"institutions":[{"id":"https://openalex.org/I1187138","display_name":"Razi University","ror":"https://ror.org/02ynb0474","country_code":"IR","type":"funder","lineage":["https://openalex.org/I1187138"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Abdolhossein Fathi","raw_affiliation_strings":["Department of Computer Engineering and Information Technology, Razi University, Kermanshah, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering and Information Technology, Razi University, Kermanshah, Iran","institution_ids":["https://openalex.org/I1187138"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5057450178"],"corresponding_institution_ids":["https://openalex.org/I1187138"],"apc_list":null,"apc_paid":null,"fwci":0.783,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.766934,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":84,"max":86},"biblio":{"volume":"54","issue":"5","first_page":"673","last_page":"696"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9996,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9996,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9993,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9993,"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/retargeting","display_name":"Retargeting","score":0.7350648},{"id":"https://openalex.org/keywords/seam-carving","display_name":"Seam carving","score":0.5584813},{"id":"https://openalex.org/keywords/quality-assessment","display_name":"Quality Assessment","score":0.43286344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7760566},{"id":"https://openalex.org/C2780575108","wikidata":"https://www.wikidata.org/wiki/Q7316652","display_name":"Retargeting","level":2,"score":0.7350648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.67376125},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.58550024},{"id":"https://openalex.org/C23746413","wikidata":"https://www.wikidata.org/wiki/Q1141379","display_name":"Seam carving","level":3,"score":0.5584813},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5281967},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5179728},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4901808},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.43286344},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33431518},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32095495},{"id":"https://openalex.org/C3018395757","wikidata":"https://www.wikidata.org/wiki/Q1379672","display_name":"Evaluation methods","level":2,"score":0.089933515},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.08991903},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1080/01969722.2022.2071408","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":57,"referenced_works":["https://openalex.org/W1755382400","https://openalex.org/W1903029394","https://openalex.org/W1963884485","https://openalex.org/W1964859077","https://openalex.org/W1971075885","https://openalex.org/W1973175507","https://openalex.org/W1985514943","https://openalex.org/W2003079626","https://openalex.org/W2016360114","https://openalex.org/W2018377917","https://openalex.org/W2030031014","https://openalex.org/W2041719651","https://openalex.org/W2055307271","https://openalex.org/W2077635163","https://openalex.org/W2103666701","https://openalex.org/W2109506130","https://openalex.org/W2121809595","https://openalex.org/W2128272608","https://openalex.org/W2133665775","https://openalex.org/W2141983208","https://openalex.org/W2151735154","https://openalex.org/W2161907179","https://openalex.org/W2161927477","https://openalex.org/W2168397407","https://openalex.org/W2235636382","https://openalex.org/W2463322449","https://openalex.org/W2508126170","https://openalex.org/W2539033431","https://openalex.org/W2566908008","https://openalex.org/W2606025925","https://openalex.org/W2606880804","https://openalex.org/W2621464029","https://openalex.org/W2742666565","https://openalex.org/W2751768166","https://openalex.org/W2763566792","https://openalex.org/W2771426268","https://openalex.org/W2793428724","https://openalex.org/W2890795004","https://openalex.org/W2895332229","https://openalex.org/W2951006004","https://openalex.org/W2966714087","https://openalex.org/W2982645234","https://openalex.org/W2990138404","https://openalex.org/W3020541733","https://openalex.org/W3127817797","https://openalex.org/W3133070173","https://openalex.org/W4210845257","https://openalex.org/W4212890593","https://openalex.org/W4232856028","https://openalex.org/W4239249262","https://openalex.org/W4243742982","https://openalex.org/W4244531973","https://openalex.org/W4247375518","https://openalex.org/W4247735191","https://openalex.org/W4249142012","https://openalex.org/W4251247712","https://openalex.org/W4365799978"],"related_works":["https://openalex.org/W4388821263","https://openalex.org/W4250433723","https://openalex.org/W2790269557","https://openalex.org/W2596972971","https://openalex.org/W2295013215","https://openalex.org/W2266217683","https://openalex.org/W2081282645","https://openalex.org/W2047755406","https://openalex.org/W2018765149","https://openalex.org/W1895742843"],"abstract_inverted_index":{"AbstractThis":[0],"paper":[1],"proposed":[2,10,91,116],"an":[3],"image":[4,25,131,157,166,174,203,213],"retargeting":[5,26,70,158],"quality":[6,35,108,139,208,220],"assessment.":[7],"In":[8],"the":[9,19,34,40,48,55,57,63,69,83,90,95,107,115,126,130,151,160,164,168,172,177,185,194,198,201,207,211],"method,":[11],"a":[12,30,102,120,138,145],"deep":[13,121],"convolution":[14],"network":[15],"is":[16],"trained":[17],"on":[18,75,150,193],"pixel":[20,152],"displacement":[21,153],"patterns":[22,154],"of":[23,36,51,59,65,89,109,114,129,179,187,200,210],"different":[24,156],"methods":[27],"to":[28,94,124,196],"produce":[29],"measure":[31],"for":[32,105],"evaluating":[33,106],"output":[37,149],"images.":[38,111],"Also,":[39],"method":[41,92,104,117,123],"extracts":[42],"three":[43],"other":[44],"measures":[45],"that":[46,132],"assess":[47],"geometric":[49,180],"changes":[50],"important":[52,127],"objects":[53,135,162,170],"in":[54,155,163,171,182],"image,":[56],"bending":[58],"block":[60],"lines,":[61],"and":[62,80,87,136,167,175,190],"extent":[64,178,186,195],"information":[66,188],"loss":[67,189],"during":[68],"process.":[71],"The":[72,112],"tests":[73],"performed":[74],"two":[76],"well-known":[77],"databases,":[78],"RetargetMe":[79],"CUHK,":[81],"demonstrate":[82],"excellent":[84],"performance,":[85],"stability,":[86],"reliability":[88],"compared":[93],"existing":[96],"methods.In":[97],"this":[98],"paper,":[99],"we":[100],"present":[101],"new":[103],"retargeted":[110,173,212],"innovations":[113],"are:":[118],"Using":[119],"learning":[122],"identify":[125],"regions":[128],"contain":[133],"foreground":[134,161],"peopleProviding":[137],"evaluation":[140],"measure,":[141],"obtained":[142],"by":[143],"training":[144],"CNN":[146],"with":[147],"regression":[148],"methodsExtracting":[159],"original":[165,202],"corresponding":[169],"determining":[176],"change":[181],"each":[183],"object.Estimating":[184],"distortion":[191],"based":[192],"which":[197],"blocks":[199],"have":[204],"been":[205],"bent.Estimating":[206],"score":[209],"using":[214],"Gaussian":[215],"process":[216],"regression.Keywords:":[217],"Deep":[218],"learningimage":[219],"assessmentimage":[221],"retargetingimportance":[222],"map":[223]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4229079333","counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2025-04-19T04:18:18.513338","created_date":"2022-05-08"}