{"id":"https://openalex.org/W2891453480","doi":"https://doi.org/10.1109/icip.2018.8451231","title":"Radio Galaxy Morphology Generation using Residual Convolutional Autoencoder and Gaussian Mixture Models","display_name":"Radio Galaxy Morphology Generation using Residual Convolutional Autoencoder and Gaussian Mixture Models","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2891453480","doi":"https://doi.org/10.1109/icip.2018.8451231","mag":"2891453480"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451231","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451231","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","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/A5102768969","display_name":"Zhixian Ma","orcid":"https://orcid.org/0000-0003-1263-9453"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhixian Ma","raw_affiliation_strings":["Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036446909","display_name":"Jie Zhu","orcid":"https://orcid.org/0000-0003-2133-4651"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhu","raw_affiliation_strings":["Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039197421","display_name":"Weitian Li","orcid":"https://orcid.org/0000-0002-7527-380X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weitian Li","raw_affiliation_strings":["Department of Astronomy, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Astronomy, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007522827","display_name":"Haiguang Xu","orcid":"https://orcid.org/0000-0001-9603-7673"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiguang Xu","raw_affiliation_strings":["Department of Astronomy, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Astronomy, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102768969"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.2089,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55282623,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"167","issue":null,"first_page":"3044","last_page":"3048"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9901000261306763,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9901000261306763,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9886000156402588,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9868999719619751,"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/autoencoder","display_name":"Autoencoder","score":0.7257509231567383},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6492173075675964},{"id":"https://openalex.org/keywords/radio-galaxy","display_name":"Radio galaxy","score":0.6003084778785706},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5673502683639526},{"id":"https://openalex.org/keywords/astrophysics","display_name":"Astrophysics","score":0.5570580959320068},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4991936683654785},{"id":"https://openalex.org/keywords/galaxy","display_name":"Galaxy","score":0.49381574988365173},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4705812335014343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4360570013523102},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42457905411720276},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.41924992203712463},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.41846901178359985},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41064274311065674},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3748709559440613},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.25407564640045166}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7257509231567383},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6492173075675964},{"id":"https://openalex.org/C20249676","wikidata":"https://www.wikidata.org/wiki/Q217012","display_name":"Radio galaxy","level":3,"score":0.6003084778785706},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5673502683639526},{"id":"https://openalex.org/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.5570580959320068},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4991936683654785},{"id":"https://openalex.org/C98444146","wikidata":"https://www.wikidata.org/wiki/Q318","display_name":"Galaxy","level":2,"score":0.49381574988365173},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4705812335014343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4360570013523102},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42457905411720276},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.41924992203712463},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.41846901178359985},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41064274311065674},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3748709559440613},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25407564640045166},{"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/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:10.1109/icip.2018.8451231","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451231","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1486632395","https://openalex.org/W1506806321","https://openalex.org/W1522301498","https://openalex.org/W1830746653","https://openalex.org/W1836465849","https://openalex.org/W1882938068","https://openalex.org/W1912512737","https://openalex.org/W2047002529","https://openalex.org/W2117233176","https://openalex.org/W2141038024","https://openalex.org/W2156387975","https://openalex.org/W2194775991","https://openalex.org/W2290770769","https://openalex.org/W2302255633","https://openalex.org/W2304648132","https://openalex.org/W2544513175","https://openalex.org/W2557283755","https://openalex.org/W2612022385","https://openalex.org/W2737163388","https://openalex.org/W2759874039","https://openalex.org/W2786198305","https://openalex.org/W2950743592","https://openalex.org/W2963093980","https://openalex.org/W2963373786","https://openalex.org/W3101816355","https://openalex.org/W3103844616","https://openalex.org/W3104968552","https://openalex.org/W4298289240","https://openalex.org/W6628849183","https://openalex.org/W6631190155","https://openalex.org/W6637568146","https://openalex.org/W6638667902","https://openalex.org/W6680858666","https://openalex.org/W6697974390","https://openalex.org/W6698183232","https://openalex.org/W6718379498"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2145836866","https://openalex.org/W2803255133","https://openalex.org/W2075383893"],"abstract_inverted_index":{"The":[0,60,133],"morphology":[1,33],"of":[2,20,116,120,141],"a":[3,32,71,89,136],"radio":[4,39,100,108],"galaxy":[5,101,109],"is":[6,146],"related":[7],"to":[8],"its":[9],"center":[10],"active":[11],"galactic":[12],"nuclei":[13],"(AGN),":[14],"which":[15,82],"can":[16,83],"reveal":[17],"the":[18,21,66,78,114,130],"evolution":[19],"super":[22],"massive":[23],"black":[24],"hole":[25],"(SMBH).":[26],"In":[27],"this":[28],"work,":[29],"we":[30,112],"propose":[31],"generation":[34],"framework":[35],"for":[36,94],"two":[37],"typical":[38],"galaxies":[40],"namely":[41,74],"Fanaroff-":[42],"Riley":[43],"type-":[44],"I":[45],"(FRI)":[46],"and":[47,55,62,123,139],"type-II":[48],"(FRII)":[49],"using":[50],"residual":[51],"convolutional":[52],"autoencoder":[53],"(RCAE)":[54],"Gaussian":[56,91],"mixture":[57],"models":[58,93],"(GMMs).":[59],"encoder":[61],"decoder":[63],"subnets":[64],"in":[65],"RCAE":[67,143],"are":[68,104],"symmetric":[69],"aside":[70],"fully-connected":[72],"layer":[73,76],"code":[75],"hosting":[77],"extracted":[79],"feature":[80,117],"vectors,":[81,118],"be":[84],"randomly":[85],"generated":[86],"later":[87],"by":[88],"three-component":[90],"Mixture":[92],"simulating":[95],"new":[96],"FRI":[97],"or":[98],"FRII":[99],"images.":[102],"Experiments":[103],"demonstrated":[105],"on":[106],"real":[107],"images,":[110],"where":[111],"discuss":[113],"length":[115],"selection":[119],"lost":[121],"functions,":[122],"make":[124],"comparisons":[125],"among":[126],"proposed":[127],"approach":[128],"with":[129],"other":[131],"networks.":[132],"results":[134],"suggest":[135],"high":[137],"efficiency":[138],"performance":[140],"our":[142],"network.":[144],"Code":[145],"available":[147],"at:":[148],"https://github.com/myinxd/rcae-gmm.":[149]},"counts_by_year":[{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}