{"id":"https://openalex.org/W4283717802","doi":"https://doi.org/10.1109/i2mtc48687.2022.9806485","title":"Infrared Image Super-Resolution via Generative Adversarial Network with Gradient Penalty Loss","display_name":"Infrared Image Super-Resolution via Generative Adversarial Network with Gradient Penalty Loss","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4283717802","doi":"https://doi.org/10.1109/i2mtc48687.2022.9806485"},"language":"en","primary_location":{"id":"doi:10.1109/i2mtc48687.2022.9806485","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc48687.2022.9806485","pdf_url":null,"source":{"id":"https://openalex.org/S4363607934","display_name":"2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-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/A5073736010","display_name":"Jian Mei","orcid":null},"institutions":[{"id":"https://openalex.org/I133270356","display_name":"Tianjin University of Technology and Education","ror":"https://ror.org/035gwtk09","country_code":"CN","type":"education","lineage":["https://openalex.org/I133270356"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Qiang Mei","raw_affiliation_strings":["School of Electronic Engineering, Tianjin University of Technology and Education,Tianjin,China","School of Electronic Engineering, Tianjin University of Technology and Education, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Tianjin University of Technology and Education,Tianjin,China","institution_ids":["https://openalex.org/I133270356"]},{"raw_affiliation_string":"School of Electronic Engineering, Tianjin University of Technology and Education, Tianjin, China","institution_ids":["https://openalex.org/I133270356"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000125775","display_name":"Xue Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I133270356","display_name":"Tianjin University of Technology and Education","ror":"https://ror.org/035gwtk09","country_code":"CN","type":"education","lineage":["https://openalex.org/I133270356"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Wen Ding","raw_affiliation_strings":["School of Electronic Engineering, Tianjin University of Technology and Education,Tianjin,China","School of Electronic Engineering, Tianjin University of Technology and Education, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Tianjin University of Technology and Education,Tianjin,China","institution_ids":["https://openalex.org/I133270356"]},{"raw_affiliation_string":"School of Electronic Engineering, Tianjin University of Technology and Education, Tianjin, China","institution_ids":["https://openalex.org/I133270356"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074225204","display_name":"Dandan Zheng","orcid":"https://orcid.org/0000-0003-2330-5221"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dandan Zheng","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University,Tianjin,China","School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034897370","display_name":"Tom Page","orcid":"https://orcid.org/0000-0002-6622-0810"},"institutions":[{"id":"https://openalex.org/I82288201","display_name":"Institute of Technology Sligo","ror":"https://ror.org/032fvf508","country_code":"IE","type":"education","lineage":["https://openalex.org/I82288201"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Tom Page","raw_affiliation_strings":["Faculty of Engineering &#x0026; Design, Institute of Technology,Dept. Computing &#x0026; Electronic Engineering,Sligo,Ireland"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering &#x0026; Design, Institute of Technology,Dept. Computing &#x0026; Electronic Engineering,Sligo,Ireland","institution_ids":["https://openalex.org/I82288201"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073736010"],"corresponding_institution_ids":["https://openalex.org/I133270356"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04406103,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991000294685364,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991000294685364,"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/T12994","display_name":"Infrared Thermography in Medicine","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.9311189651489258},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.711268961429596},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6545180678367615},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5541113615036011},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5270093679428101},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5264540314674377},{"id":"https://openalex.org/keywords/radiance","display_name":"Radiance","score":0.5046638250350952},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4690556824207306},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.429220974445343},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4126417934894562},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3664170503616333},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.2565946877002716},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11531612277030945}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.9311189651489258},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.711268961429596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6545180678367615},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5541113615036011},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5270093679428101},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5264540314674377},{"id":"https://openalex.org/C23690007","wikidata":"https://www.wikidata.org/wiki/Q1411145","display_name":"Radiance","level":2,"score":0.5046638250350952},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4690556824207306},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.429220974445343},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4126417934894562},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3664170503616333},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.2565946877002716},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11531612277030945},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/i2mtc48687.2022.9806485","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc48687.2022.9806485","pdf_url":null,"source":{"id":"https://openalex.org/S4363607934","display_name":"2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W2015148749","https://openalex.org/W2040739536","https://openalex.org/W2077332544","https://openalex.org/W2130150012","https://openalex.org/W2246990146","https://openalex.org/W2280406817","https://openalex.org/W2313938314","https://openalex.org/W2345844278","https://openalex.org/W2575376020","https://openalex.org/W2600673109","https://openalex.org/W2606785846","https://openalex.org/W2612808384","https://openalex.org/W2738334925","https://openalex.org/W2789118608","https://openalex.org/W2804333250","https://openalex.org/W2809795042","https://openalex.org/W2886688927","https://openalex.org/W2890609887","https://openalex.org/W2913392736","https://openalex.org/W2938386730","https://openalex.org/W2963470893","https://openalex.org/W2964201867","https://openalex.org/W2965846399","https://openalex.org/W2980606026","https://openalex.org/W3214017641","https://openalex.org/W4295521014","https://openalex.org/W4298289240","https://openalex.org/W6637568146","https://openalex.org/W6690941987","https://openalex.org/W6732249622","https://openalex.org/W6735913928","https://openalex.org/W6738080645","https://openalex.org/W6761784800","https://openalex.org/W6766542789","https://openalex.org/W6779669310","https://openalex.org/W6804232624"],"related_works":["https://openalex.org/W4293320219","https://openalex.org/W2953246223","https://openalex.org/W3110074278","https://openalex.org/W4283584549","https://openalex.org/W2554314924","https://openalex.org/W4288256692","https://openalex.org/W2998859928","https://openalex.org/W3156863413","https://openalex.org/W4381885966","https://openalex.org/W2969399009"],"abstract_inverted_index":{"Infrared":[0],"thermal":[1],"imaging":[2],"technology":[3],"has":[4,139],"been":[5],"gradually":[6],"developed":[7],"and":[8,13,20,32,52,67,99,127,151],"widely":[9,106],"applied":[10],"in":[11],"measurement":[12,152],"non-destructive":[14,149],"testing.":[15],"However,":[16],"low-contrast":[17],"blurred":[18],"details":[19],"expensive":[21],"acquisition":[22],"equipment":[23],"remain":[24],"as":[25],"barriers":[26],"to":[27,47,70,92,96],"its":[28],"further":[29],"practical":[30],"applications":[31],"widespread":[33],"adoption.":[34],"In":[35],"this":[36,137],"paper,":[37],"a":[38,49,73,82,142],"novel":[39],"framework":[40],"comprising":[41],"deep":[42,145],"learning":[43,146],"techniques":[44],"is":[45,65,87],"proposed":[46,111],"offer":[48],"relatively":[50],"competitive":[51],"compatible":[53],"solution":[54],"of":[55,104,136,144],"infrared":[56,108,148],"image":[57],"super-resolution.":[58],"Firstly,":[59],"radiance":[60],"information":[61],"from":[62],"low-resolution":[63],"imagery":[64],"detected":[66],"automatically":[68],"translated":[69],"high-resolution":[71],"through":[72],"Generative":[74],"Adversarial":[75],"Network":[76],"(GAN)":[77],"with":[78,120],"Wasserstein":[79],"distance.":[80],"Secondly,":[81],"gradient":[83],"penalty":[84],"loss":[85],"function":[86],"utilized":[88,107],"for":[89,141],"the":[90,94,110,117],"discriminator":[91],"guide":[93],"generator":[95],"achieve":[97],"reasonable":[98],"acceptable":[100],"convergence.":[101],"Through":[102],"evaluation":[103],"three":[105],"datasets,":[109],"method":[112,119],"demonstrates":[113],"superior":[114],"performance":[115],"against":[116],"state-of-art":[118],"more":[121],"accurate":[122],"Peak":[123],"Signal-To-Noise":[124],"Ratio":[125],"(PSNR)":[126],"Structural":[128],"Similarity":[129],"Index":[130],"Measure":[131],"(SSIM)":[132],"respectively.":[133],"The":[134],"outcome":[135],"study":[138],"implications":[140],"real-application":[143],"based":[147],"testing":[150],"scenarios.":[153]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
