{"id":"https://openalex.org/W4411295410","doi":"https://doi.org/10.1142/s0218001425520159","title":"Jaya-Waterwheel Plant Algorithm with Hybrid Deep Learning and Probabilistic Fusion for Image Inpainting","display_name":"Jaya-Waterwheel Plant Algorithm with Hybrid Deep Learning and Probabilistic Fusion for Image Inpainting","publication_year":2025,"publication_date":"2025-06-13","ids":{"openalex":"https://openalex.org/W4411295410","doi":"https://doi.org/10.1142/s0218001425520159"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001425520159","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001425520159","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},"type":"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/A5008407340","display_name":"T M Sivanesan","orcid":null},"institutions":[{"id":"https://openalex.org/I1330855593","display_name":"Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology","ror":"https://ror.org/05bc5bx80","country_code":"IN","type":"education","lineage":["https://openalex.org/I1330855593"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"T. M. Sivanesan","raw_affiliation_strings":["Department of Computer Science & Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Tamil Nadu 600062, India"],"raw_orcid":"https://orcid.org/0000-0002-7497-0275","affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Tamil Nadu 600062, India","institution_ids":["https://openalex.org/I1330855593"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000789897","display_name":"N. Vijayaraj","orcid":null},"institutions":[{"id":"https://openalex.org/I1330855593","display_name":"Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology","ror":"https://ror.org/05bc5bx80","country_code":"IN","type":"education","lineage":["https://openalex.org/I1330855593"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"N. Vijayaraj","raw_affiliation_strings":["Department of Computer Science & Engineering/Faculty, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Tamil Nadu 600062, India"],"raw_orcid":"https://orcid.org/0000-0001-7450-4963","affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering/Faculty, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Tamil Nadu 600062, India","institution_ids":["https://openalex.org/I1330855593"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5008407340"],"corresponding_institution_ids":["https://openalex.org/I1330855593"],"apc_list":null,"apc_paid":null,"fwci":1.1332,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.78850063,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"39","issue":"12","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9524000287055969,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9524000287055969,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9456999897956848,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9437000155448914,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inpainting","display_name":"Inpainting","score":0.9113572835922241},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.699852705001831},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.632197916507721},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5668284296989441},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5401012897491455},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46008017659187317},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45498552918434143},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4528648257255554},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3821592330932617},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.355984091758728},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33363401889801025}],"concepts":[{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.9113572835922241},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.699852705001831},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.632197916507721},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5668284296989441},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5401012897491455},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46008017659187317},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45498552918434143},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4528648257255554},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3821592330932617},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.355984091758728},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33363401889801025},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001425520159","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001425520159","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W89341001","https://openalex.org/W1755572302","https://openalex.org/W1975049209","https://openalex.org/W2085048703","https://openalex.org/W2613155248","https://openalex.org/W2738588019","https://openalex.org/W2740494144","https://openalex.org/W2798365772","https://openalex.org/W2963420272","https://openalex.org/W2963917315","https://openalex.org/W2964540618","https://openalex.org/W3005930772","https://openalex.org/W3032190803","https://openalex.org/W3035426499","https://openalex.org/W3041324976","https://openalex.org/W3043547428","https://openalex.org/W3099925406","https://openalex.org/W3102846047","https://openalex.org/W3118919735","https://openalex.org/W4224312287","https://openalex.org/W4288751245","https://openalex.org/W4313154016","https://openalex.org/W4376956048","https://openalex.org/W4390954029","https://openalex.org/W4391035760","https://openalex.org/W4402203509","https://openalex.org/W4402916127","https://openalex.org/W4409019551","https://openalex.org/W4409475672"],"related_works":["https://openalex.org/W2017457812","https://openalex.org/W3178025616","https://openalex.org/W2060947339","https://openalex.org/W2131831293","https://openalex.org/W2946160871","https://openalex.org/W3035059915","https://openalex.org/W1995073329","https://openalex.org/W425542480","https://openalex.org/W49967185","https://openalex.org/W2107727507"],"abstract_inverted_index":{"This":[0],"study":[1],"introduces":[2],"a":[3,59,71,78,87,114],"memory-efficient":[4],"and":[5,45,50,77,93,99,127],"high-resolution":[6],"image":[7,52,62,107],"inpainting":[8,69],"framework":[9],"called":[10],"Jaya":[11,91],"Waterwheel":[12,95],"Plant":[13,96],"Algorithm-Hybrid":[14],"Context":[15],"Deep":[16,27],"Learning":[17,28],"(JWWPA-Hybrid":[18],"DL).":[19],"Designed":[20],"to":[21,37,135],"address":[22],"the":[23,40,64,84,90,94,102],"limitations":[24],"of":[25,89,116,120,125,129],"conventional":[26],"(DL)":[29],"models":[30],"that":[31],"handle":[32],"only":[33],"low-resolution":[34],"images":[35],"due":[36],"memory":[38],"constraints,":[39],"proposed":[41,110],"method":[42],"integrates":[43],"optimization":[44],"DL":[46,112],"for":[47],"more":[48],"accurate":[49],"realistic":[51],"restoration.":[53],"The":[54,109],"workflow":[55],"involves:":[56],"(1)":[57],"acquiring":[58],"damaged":[60],"input":[61],"from":[63],"Figshare":[65],"database,":[66],"(2)":[67],"applying":[68],"via":[70],"Context-Conditional":[72],"Generative":[73],"Adversarial":[74],"Networks":[75],"(CC-GAN)":[76],"context":[79],"encoder,":[80],"both":[81],"optimized":[82],"using":[83],"JWWPA":[85],"\u2014":[86],"hybrid":[88],"algorithm":[92],"Algorithm":[97],"(WWPA),":[98],"(3)":[100],"combining":[101],"outputs":[103],"through":[104],"probabilistic":[105],"function-based":[106],"fusion.":[108],"JWWPA-Hybrid":[111],"achieves":[113],"PSNR":[115],"38.555":[117],"dB,":[118],"SDME":[119],"58.472[Formula:":[121],"see":[122],"text]dB,":[123],"SSIM":[124],"0.817,":[126],"UQI":[128],"0.827,":[130],"demonstrating":[131],"superior":[132],"performance":[133],"compared":[134],"existing":[136],"approaches.":[137]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}