{"id":"https://openalex.org/W3090149108","doi":"https://doi.org/10.1109/icip40778.2020.9191030","title":"Development Of New Fractal And Non-Fractal Deep Residual Networks For Deblocking Of Jpeg Decompressed Images","display_name":"Development Of New Fractal And Non-Fractal Deep Residual Networks For Deblocking Of Jpeg Decompressed Images","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3090149108","doi":"https://doi.org/10.1109/icip40778.2020.9191030","mag":"3090149108"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191030","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 Image Processing (ICIP)","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/A5074650143","display_name":"Alireza Esmaeilzehi","orcid":"https://orcid.org/0000-0002-3625-1608"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alireza Esmaeilzehi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068820891","display_name":"M. Omair Ahmad","orcid":"https://orcid.org/0000-0002-2924-6659"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"M. Omair Ahmad","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013967994","display_name":"M.N.S. Swamy","orcid":"https://orcid.org/0000-0002-3989-5476"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"M.N.S. Swamy","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1271","last_page":"1275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","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/T10688","display_name":"Image and Signal Denoising Methods","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/T11105","display_name":"Advanced Image Processing Techniques","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/T11165","display_name":"Image and Video Quality Assessment","score":0.9997000098228455,"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/deblocking-filter","display_name":"Deblocking filter","score":0.9544927477836609},{"id":"https://openalex.org/keywords/jpeg","display_name":"JPEG","score":0.8327686786651611},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.8286877870559692},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7285658121109009},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6548858880996704},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5900469422340393},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5238333344459534},{"id":"https://openalex.org/keywords/transform-coding","display_name":"Transform coding","score":0.5011959075927734},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4889189302921295},{"id":"https://openalex.org/keywords/compression-artifact","display_name":"Compression artifact","score":0.46794313192367554},{"id":"https://openalex.org/keywords/blocking","display_name":"Blocking (statistics)","score":0.4187447428703308},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.37402743101119995},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35129761695861816},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2992051839828491},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.28220468759536743},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2580547332763672},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22821864485740662},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.2100485861301422},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15045028924942017}],"concepts":[{"id":"https://openalex.org/C143184774","wikidata":"https://www.wikidata.org/wiki/Q3020846","display_name":"Deblocking filter","level":2,"score":0.9544927477836609},{"id":"https://openalex.org/C198751489","wikidata":"https://www.wikidata.org/wiki/Q2195","display_name":"JPEG","level":3,"score":0.8327686786651611},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8286877870559692},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7285658121109009},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6548858880996704},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5900469422340393},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5238333344459534},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.5011959075927734},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4889189302921295},{"id":"https://openalex.org/C57654395","wikidata":"https://www.wikidata.org/wiki/Q1097775","display_name":"Compression artifact","level":5,"score":0.46794313192367554},{"id":"https://openalex.org/C144745244","wikidata":"https://www.wikidata.org/wiki/Q4927286","display_name":"Blocking (statistics)","level":2,"score":0.4187447428703308},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.37402743101119995},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35129761695861816},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2992051839828491},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.28220468759536743},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2580547332763672},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22821864485740662},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.2100485861301422},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15045028924942017},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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":1,"locations":[{"id":"doi:10.1109/icip40778.2020.9191030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191030","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 Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1815076433","https://openalex.org/W1906770428","https://openalex.org/W2121927366","https://openalex.org/W2142683286","https://openalex.org/W2194775991","https://openalex.org/W2408279554","https://openalex.org/W2466611277","https://openalex.org/W2508457857","https://openalex.org/W2519021537","https://openalex.org/W2557283755","https://openalex.org/W2884569173","https://openalex.org/W2919115771","https://openalex.org/W2955519013","https://openalex.org/W2963372104","https://openalex.org/W2970009752","https://openalex.org/W2987869089","https://openalex.org/W2999418043","https://openalex.org/W3182211633","https://openalex.org/W6638545294","https://openalex.org/W6714181750"],"related_works":["https://openalex.org/W3109737331","https://openalex.org/W3016393364","https://openalex.org/W2962930383","https://openalex.org/W4287814353","https://openalex.org/W3090149108","https://openalex.org/W2536414725","https://openalex.org/W2545896937","https://openalex.org/W2111280862","https://openalex.org/W2612631671","https://openalex.org/W2081477649"],"abstract_inverted_index":{"The":[0,81,107,131,153],"JPEG":[1,12,23,51,151],"compression":[2],"scheme":[3],"introduces":[4],"blocking":[5],"artifacts":[6],"when":[7],"the":[8,63,88,120,124,128,148,156,160,170],"images":[9],"are":[10],"decompressed.":[11],"image":[13,25,52],"deblocking":[14,53,163,173],"schemes":[15],"based":[16],"on":[17,159],"deep":[18,50],"neural":[19,145],"networks":[20,146,164],"map":[21],"a":[22,32,40,49,111],"decompressed":[24],"to":[26,98],"its":[27,57,93],"corresponding":[28],"deblocked":[29],"image.":[30],"Employing":[31],"residual":[33,46,72,79,83,102,113,134],"block":[34,84,114,126,129],"that":[35,74,115],"is":[36,110,116],"capable":[37],"of":[38,43,92,150,155],"generating":[39,99],"rich":[41,76],"set":[42],"high":[44,77,89],"frequency":[45,78,90],"features":[47,86,103],"in":[48,96,123,139],"network":[54,64],"can":[55],"improve":[56],"representational":[58],"capability,":[59],"and":[60,142],"therefore,":[61],"enhance":[62],"performance.":[65],"In":[66],"this":[67],"paper,":[68],"we":[69],"propose":[70],"two":[71,132,161],"blocks":[73,135],"generate":[75],"features.":[80],"first":[82,125],"generates":[85],"from":[87],"component":[91],"input":[94],"signal":[95],"addition":[97],"conventional":[100,121],"hierarchical":[101],"using":[104],"convolutional":[105],"operations.":[106],"second":[108],"one":[109],"fractal":[112],"developed":[117],"by":[118,127],"replacing":[119],"convolutions":[122],"itself.":[130],"proposed":[133,162],"are,":[136],"respectively,":[137],"used":[138],"recursive":[140],"(non-fractal)":[141],"non-recursive":[143],"(fractal)":[144],"for":[147],"task":[149],"deblocking.":[152],"results":[154],"experiments":[157],"performed":[158],"show":[165],"their":[166],"performance":[167],"superiority":[168],"over":[169],"respective":[171],"state-of-the-art":[172],"networks.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
