{"id":"https://openalex.org/W3001607327","doi":"https://doi.org/10.1109/cisp-bmei48845.2019.8965902","title":"Remote Sensing Image Colorization Based on Multiscale SEnet GAN","display_name":"Remote Sensing Image Colorization Based on Multiscale SEnet GAN","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W3001607327","doi":"https://doi.org/10.1109/cisp-bmei48845.2019.8965902","mag":"3001607327"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei48845.2019.8965902","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei48845.2019.8965902","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5101596422","display_name":"Min Wu","orcid":"https://orcid.org/0000-0002-9419-6088"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Min Wu","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, Yunnan, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, Yunnan, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100641350","display_name":"Xin Jin","orcid":"https://orcid.org/0000-0003-2211-2006"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Jin","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, Yunnan, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, Yunnan, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039717115","display_name":"Qian Jiang","orcid":"https://orcid.org/0000-0003-3097-0721"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Jiang","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, Yunnan, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, Yunnan, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052639662","display_name":"Shin\u2010Jye Lee","orcid":"https://orcid.org/0000-0003-4265-5016"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shin-Jye Lee","raw_affiliation_strings":["Institute of Technology Management, National Chiao Tung University, Hsinchu, Taiwan, China"],"affiliations":[{"raw_affiliation_string":"Institute of Technology Management, National Chiao Tung University, Hsinchu, Taiwan, China","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101959950","display_name":"Lin Guo","orcid":"https://orcid.org/0000-0001-5689-1760"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Guo","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, Yunnan, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, Yunnan, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042445231","display_name":"Yide Di","orcid":"https://orcid.org/0000-0003-3802-6620"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yide Di","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, Yunnan, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, Yunnan, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101751786","display_name":"Shanshan Huang","orcid":"https://orcid.org/0000-0001-7893-3861"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanshan Huang","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, Yunnan, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, Yunnan, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100979140","display_name":"Jinfang Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinfang Huang","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, Yunnan, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, Yunnan, China","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5101596422"],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":null,"apc_paid":null,"fwci":0.5061,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.7042249,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9969000220298767,"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":0.9969000220298767,"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":0.9950000047683716,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9747999906539917,"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/grayscale","display_name":"Grayscale","score":0.7646006345748901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7259689569473267},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.704104483127594},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6815906167030334},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6783962249755859},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.67070472240448},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6613534688949585},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5451109409332275},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5413089394569397},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.45038771629333496},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3438710868358612},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.32755088806152344},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1298004388809204},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11753353476524353},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06869515776634216}],"concepts":[{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.7646006345748901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7259689569473267},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.704104483127594},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6815906167030334},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6783962249755859},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.67070472240448},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6613534688949585},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5451109409332275},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5413089394569397},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.45038771629333496},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3438710868358612},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.32755088806152344},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1298004388809204},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11753353476524353},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06869515776634216},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei48845.2019.8965902","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei48845.2019.8965902","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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":26,"referenced_works":["https://openalex.org/W179875071","https://openalex.org/W2005964300","https://openalex.org/W2064076387","https://openalex.org/W2136154655","https://openalex.org/W2194775991","https://openalex.org/W2240798854","https://openalex.org/W2242218935","https://openalex.org/W2295537950","https://openalex.org/W2326925005","https://openalex.org/W2432912172","https://openalex.org/W2461158874","https://openalex.org/W2590274298","https://openalex.org/W2608029800","https://openalex.org/W2613155248","https://openalex.org/W2623526899","https://openalex.org/W2708692267","https://openalex.org/W2728047984","https://openalex.org/W2741785014","https://openalex.org/W2743780012","https://openalex.org/W2752782242","https://openalex.org/W2792021479","https://openalex.org/W2957365494","https://openalex.org/W2963420686","https://openalex.org/W3102726805","https://openalex.org/W4320013936","https://openalex.org/W6607333740"],"related_works":["https://openalex.org/W115686965","https://openalex.org/W2768918307","https://openalex.org/W2788191623","https://openalex.org/W3151908889","https://openalex.org/W2946952476","https://openalex.org/W4200417262","https://openalex.org/W4308217387","https://openalex.org/W2904616728","https://openalex.org/W4224217118","https://openalex.org/W2974859913"],"abstract_inverted_index":{"Image":[0],"colorization":[1,38,106,130],"technique":[2],"is":[3,24,62],"to":[4,56,64],"colorize":[5],"the":[6,13,18,65,70,75,80,83,90,94,100,109,113,129],"grayscale":[7],"images":[8,23],"or":[9],"single-channel":[10],"images.":[11,134],"In":[12],"research":[14],"of":[15,20,34,67,82,131],"image":[16,37,77,105,125],"colorization,":[17],"coloring":[19],"remote":[21,35,132],"sensing":[22,36,133],"a":[25,31,58,117],"challenging":[26],"problem.":[27],"This":[28],"paper":[29],"proposes":[30],"new":[32,59],"method":[33,39,102,115],"based":[40],"on":[41,120,128],"Deep":[42],"Convolution":[43],"Generative":[44],"Adversarial":[45],"Network":[46],"(DCGAN).":[47],"We":[48,97],"combine":[49],"multi-scale":[50],"convolution":[51],"with":[52,103],"Squeeze-and-Excitation":[53],"Networks":[54],"(SEnet)":[55],"propose":[57],"model":[60],"that":[61,112],"applied":[63],"generator":[66,71],"DCGAN.":[68],"Therefore,":[69],"not":[72],"only":[73],"retains":[74],"largest":[76],"features":[78],"in":[79,93],"process":[81],"generating":[84],"images,":[85],"but":[86],"also":[87],"can":[88],"adjust":[89],"channel":[91],"weights":[92],"training":[95],"process.":[96],"have":[98],"compared":[99],"proposed":[101,114],"other":[104],"methods,":[107],"and":[108,124],"results":[110],"show":[111],"has":[116],"good":[118],"performance":[119],"both":[121],"human":[122],"vision":[123],"evaluation":[126],"indicators":[127]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}