{"id":"https://openalex.org/W4388891111","doi":"https://doi.org/10.48550/arxiv.2311.11286","title":"Classification of Radio Galaxies with trainable COSFIRE filters","display_name":"Classification of Radio Galaxies with trainable COSFIRE filters","publication_year":2023,"publication_date":"2023-11-19","ids":{"openalex":"https://openalex.org/W4388891111","doi":"https://doi.org/10.48550/arxiv.2311.11286"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2311.11286","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.11286","pdf_url":"https://arxiv.org/pdf/2311.11286","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2311.11286","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017153016","display_name":"Steven Ndung'u","orcid":"https://orcid.org/0000-0002-4197-1837","observed_orcids":["https://orcid.org/0000-0002-4197-1837"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ndungu, Steven","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058690922","display_name":"Trienko Grobler","orcid":"https://orcid.org/0000-0001-5274-0105","observed_orcids":["https://orcid.org/0000-0001-5274-0105"]},"institutions":[{"id":"https://openalex.org/I26092322","display_name":"Stellenbosch University","ror":"https://ror.org/05bk57929","country_code":"ZA","type":"education","lineage":["https://openalex.org/I26092322"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Grobler, Trienko","raw_affiliation_strings":["University of Stellenbosch , Cnr Banhoek Road & Joubert Street , Stellenbosch , 7600 , South Africa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Stellenbosch , Cnr Banhoek Road & Joubert Street , Stellenbosch , 7600 , South Africa","institution_ids":["https://openalex.org/I26092322"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033565717","display_name":"Stefan J. Wijnholds","orcid":"https://orcid.org/0000-0002-0463-3011","observed_orcids":["https://orcid.org/0000-0002-0463-3011"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karastoyanova, Stefan J. Wijnholds Dimka","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5027326994","display_name":"George Azzopardi","orcid":"https://orcid.org/0000-0001-6552-2596","observed_orcids":["https://orcid.org/0000-0001-6552-2596"]},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Azzopardi, George","raw_affiliation_strings":["University of Groningen , N\u0133enborgh 9 , 9712 CP , Groningen , The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Groningen , N\u0133enborgh 9 , 9712 CP , Groningen , The Netherlands","institution_ids":["https://openalex.org/I169381384"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10026","display_name":"Galaxies: Formation, Evolution, Phenomena","score":0.5835000276565552,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10026","display_name":"Galaxies: Formation, Evolution, Phenomena","score":0.5835000276565552,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12450","display_name":"Radio Astronomy Observations and Technology","score":0.14480000734329224,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.0722000002861023,"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/radio-galaxy-classification","display_name":"radio galaxy classification","score":0.8629999756813049},{"id":"https://openalex.org/keywords/galaxy-morphology","display_name":"galaxy morphology","score":0.5910000205039978},{"id":"https://openalex.org/keywords/computational-efficiency","display_name":"computational efficiency","score":0.5600000023841858},{"id":"https://openalex.org/keywords/radio-galaxy-morphology","display_name":"radio galaxy morphology","score":0.4749999940395355}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6768431067466736},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6092735528945923},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.5492161512374878},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.531606912612915},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5259029269218445},{"id":"https://openalex.org/C98444146","wikidata":"https://www.wikidata.org/wiki/Q318","display_name":"Galaxy","level":2,"score":0.4990813732147217},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.46546483039855957},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4495748281478882},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.448916494846344},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.429516077041626},{"id":"https://openalex.org/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.24643096327781677},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.17013242840766907},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.14382466673851013},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12200036644935608},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0924835205078125},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0903325080871582},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2311.11286","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.11286","pdf_url":"https://arxiv.org/pdf/2311.11286","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2311.11286","doi":"https://doi.org/10.48550/arxiv.2311.11286","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2311.11286","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2311.11286","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.11286","pdf_url":"https://arxiv.org/pdf/2311.11286","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G4026487633","display_name":null,"funder_award_id":"119488","funder_id":"https://openalex.org/F4320320671","funder_display_name":"National Research Foundation"},{"id":"https://openalex.org/G8991205595","display_name":null,"funder_award_id":"CSRP2204224243","funder_id":"https://openalex.org/F4320320671","funder_display_name":"National Research Foundation"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320320933","display_name":"Rijksuniversiteit Groningen","ror":"https://ror.org/012p63287"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388891111.pdf","grobid_xml":"https://content.openalex.org/works/W4388891111.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3110089626","https://openalex.org/W2884327410","https://openalex.org/W3135185658","https://openalex.org/W4283705601","https://openalex.org/W2612022385","https://openalex.org/W4403729605","https://openalex.org/W3163062636","https://openalex.org/W4362568649","https://openalex.org/W4413957337","https://openalex.org/W7128031796"],"abstract_inverted_index":{"Radio":[0],"galaxies":[1],"exhibit":[2],"a":[3,13,27,77,92,185],"rich":[4],"diversity":[5],"of":[6,15,60,85,99,115,162],"characteristics":[7],"and":[8,58,73,103,124],"emit":[9],"radio":[10,41,94,173,195],"emissions":[11],"through":[12],"variety":[14],"radiation":[16],"mechanisms,":[17],"making":[18],"their":[19],"classification":[20,43,210],"into":[21],"distinct":[22],"types":[23],"based":[24],"on":[25,91,132],"morphology":[26],"complex":[28],"challenge.":[29],"To":[30,81],"address":[31],"this":[32,133],"challenge":[33],"effectively,":[34],"we":[35,88],"introduce":[36],"an":[37,111],"innovative":[38],"approach":[39,67,109,166],"for":[40],"galaxy":[42,95,174,196],"using":[44],"COSFIRE":[45,66,137,164],"filters.":[46],"These":[47],"filters":[48,138],"possess":[49],"the":[50,56,83,127,147,154,160,163,169,181,190],"ability":[51],"to":[52,54,179,194,207],"adapt":[53],"both":[55],"shape":[57],"orientation":[59,191],"prototype":[61],"patterns":[62],"within":[63],"images.":[64],"The":[65],"is":[68,126,200,205],"explainable,":[69],"learning-free,":[70],"rotation-tolerant,":[71],"efficient,":[72],"does":[74],"not":[75],"require":[76],"huge":[78],"training":[79,101],"set.":[80,135],"assess":[82],"efficacy":[84],"our":[86,108],"method,":[87],"conducted":[89],"experiments":[90],"benchmark":[93],"data":[96,134],"set":[97],"comprising":[98],"1180":[100],"samples":[102],"404":[104],"test":[105],"samples.":[106],"Notably,":[107],"achieved":[110,131],"average":[112],"accuracy":[113],"rate":[114],"93.36\\%.":[116],"This":[117,176],"achievement":[118],"outperforms":[119],"contemporary":[120],"deep":[121],"learning":[122],"models,":[123],"it":[125,204],"best":[128],"result":[129],"ever":[130],"Additionally,":[136],"offer":[139],"better":[140],"computational":[141],"performance,":[142],"$\\sim$20$\\times$":[143],"fewer":[144],"operations":[145],"than":[146],"DenseNet-based":[148],"competing":[149],"method":[150,199],"(when":[151],"comparing":[152],"at":[153],"same":[155],"accuracy).":[156],"Our":[157,198],"findings":[158],"underscore":[159],"effectiveness":[161],"filter-based":[165],"in":[167,202],"addressing":[168],"complexities":[170],"associated":[171],"with":[172],"classification.":[175],"research":[177],"contributes":[178],"advancing":[180],"field":[182],"by":[183],"offering":[184],"robust":[186],"solution":[187],"that":[188,203],"transcends":[189],"challenges":[192],"intrinsic":[193],"observations.":[197],"versatile":[201],"applicable":[206],"various":[208],"image":[209],"approaches.":[211]},"counts_by_year":[],"updated_date":"2026-10-13T10:08:12.033832","created_date":"2023-11-22T00:00:00"}