{"id":"https://openalex.org/W7118195770","doi":"https://doi.org/10.1007/s11263-025-02658-2","title":"A Lightweight Hybrid Gabor Deep Learning Approach and its Application to Medical Image Classification","display_name":"A Lightweight Hybrid Gabor Deep Learning Approach and its Application to Medical Image Classification","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7118195770","doi":"https://doi.org/10.1007/s11263-025-02658-2"},"language":"en","primary_location":{"id":"doi:10.1007/s11263-025-02658-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11263-025-02658-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-025-02658-2.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11263-025-02658-2.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121951592","display_name":"Rayyan Ahmed","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]}],"countries":["QA"],"is_corresponding":true,"raw_author_name":"Rayyan Ahmed","raw_affiliation_strings":["Information and Computing Technology Division, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar"],"raw_orcid":"https://orcid.org/0000-0003-2218-152X","affiliations":[{"raw_affiliation_string":"Information and Computing Technology Division, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121945713","display_name":"Hamza Baali","orcid":null},"institutions":[{"id":"https://openalex.org/I5681781","display_name":"The University of Adelaide","ror":"https://ror.org/00892tw58","country_code":"AU","type":"education","lineage":["https://openalex.org/I5681781"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hamza Baali","raw_affiliation_strings":["School of Electrical and Mechanical Engineering, University of Adelaide, North Terrace, Adelaide, SA, 5005, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Mechanical Engineering, University of Adelaide, North Terrace, Adelaide, SA, 5005, Australia","institution_ids":["https://openalex.org/I5681781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072662577","display_name":"Abdesselam Bouzerdoum","orcid":"https://orcid.org/0000-0002-9163-0045"},"institutions":[{"id":"https://openalex.org/I204824540","display_name":"University of Wollongong","ror":"https://ror.org/00jtmb277","country_code":"AU","type":"education","lineage":["https://openalex.org/I204824540"]},{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]}],"countries":["AU","QA"],"is_corresponding":false,"raw_author_name":"Abdesselam Bouzerdoum","raw_affiliation_strings":["Information and Computing Technology Division, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar","School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW, 2522, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information and Computing Technology Division, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839"]},{"raw_affiliation_string":"School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW, 2522, Australia","institution_ids":["https://openalex.org/I204824540"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5121951592"],"corresponding_institution_ids":["https://openalex.org/I4210144839"],"apc_list":{"value":2890,"currency":"EUR","value_usd":3690},"apc_paid":{"value":2890,"currency":"EUR","value_usd":3690},"fwci":16.3679,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.96027935,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"134","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.10450000315904617,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.10450000315904617,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.06809999793767929,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.050999999046325684,"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/robustness","display_name":"Robustness (evolution)","score":0.6751000285148621},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.595300018787384},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5935999751091003},{"id":"https://openalex.org/keywords/gabor-filter","display_name":"Gabor filter","score":0.578000009059906},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5371000170707703},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5171999931335449},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.46399998664855957},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4417000114917755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7996000051498413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7594000101089478},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6751000285148621},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.595300018787384},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5935999751091003},{"id":"https://openalex.org/C2779883129","wikidata":"https://www.wikidata.org/wiki/Q2447890","display_name":"Gabor filter","level":3,"score":0.578000009059906},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5371000170707703},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5171999931335449},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.46399998664855957},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4417000114917755},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.3804999887943268},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3709999918937683},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3700999915599823},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3165999948978424},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3075999915599823},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2973000109195709},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2856000065803528},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.2766000032424927},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2709999978542328},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C121475858","wikidata":"https://www.wikidata.org/wiki/Q2735911","display_name":"Spatial filter","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C100515483","wikidata":"https://www.wikidata.org/wiki/Q3268235","display_name":"Filter bank","level":3,"score":0.2578999996185303}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11263-025-02658-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11263-025-02658-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-025-02658-2.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11263-025-02658-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11263-025-02658-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-025-02658-2.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.4907529950141907}],"awards":[{"id":"https://openalex.org/G8250848454","display_name":null,"funder_award_id":"GSRA8-L-1-0428-21018]","funder_id":"https://openalex.org/F4320332753","funder_display_name":"Qatar National Research Fund"}],"funders":[{"id":"https://openalex.org/F4320309815","display_name":"Qatar Foundation","ror":"https://ror.org/01cawbq05"},{"id":"https://openalex.org/F4320319188","display_name":"Hamad Bin Khalifa University","ror":"https://ror.org/03eyq4y97"},{"id":"https://openalex.org/F4320321038","display_name":"Fonds National de la Recherche Luxembourg","ror":"https://ror.org/039z13y21"},{"id":"https://openalex.org/F4320332753","display_name":"Qatar National Research Fund","ror":"https://ror.org/01svaqq28"},{"id":"https://openalex.org/F4320334468","display_name":"Qatar National Library","ror":"https://ror.org/02jv93662"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7118195770.pdf","grobid_xml":"https://content.openalex.org/works/W7118195770.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2063603851","https://openalex.org/W2137475834","https://openalex.org/W2784765879","https://openalex.org/W2956057111","https://openalex.org/W2992234530","https://openalex.org/W3011763265","https://openalex.org/W3211191383","https://openalex.org/W4205494850","https://openalex.org/W4224921465","https://openalex.org/W4313399775","https://openalex.org/W4317436377","https://openalex.org/W4324144441","https://openalex.org/W4378378836","https://openalex.org/W4385444515","https://openalex.org/W4387745623","https://openalex.org/W4390871942","https://openalex.org/W4398977093","https://openalex.org/W4399714957","https://openalex.org/W4400148181","https://openalex.org/W4401337541","https://openalex.org/W4402215456","https://openalex.org/W4404009528","https://openalex.org/W4405915982","https://openalex.org/W4407681094","https://openalex.org/W4408292837"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Deep":[1],"learning":[2,226],"has":[3],"revolutionized":[4],"image":[5],"analysis,":[6],"but":[7],"its":[8],"applications":[9],"are":[10],"limited":[11],"by":[12],"the":[13,76],"need":[14],"for":[15,58,115,230],"large":[16],"datasets":[17],"and":[18,40,62,82,91,106,121,136,151,163,174,178,204,242],"high":[19],"computational":[20],"resources.":[21],"Hybrid":[22],"approaches":[23],"that":[24],"combine":[25],"domain-specific,":[26],"universal":[27],"feature":[28,60,96,146],"extractor":[29],"with":[30,54,71,160,224],"learnable":[31],"neural":[32,56],"networks":[33,57,143],"offer":[34],"a":[35,45,49],"promising":[36],"balance":[37,80],"of":[38],"efficiency":[39,229],"accuracy.":[41],"This":[42,218],"paper":[43],"presents":[44],"hybrid":[46,167],"model":[47,124,168],"integrating":[48,221],"Gabor":[50,64],"filter":[51,244],"bank":[52],"front-end":[53],"compact":[55],"efficient":[59],"extraction":[61],"classification.":[63],"filters,":[65],"inherently":[66],"bandpass,":[67],"extract":[68],"early-stage":[69],"features":[70,223],"spatially":[72],"shifted":[73],"filters":[74],"covering":[75],"frequency":[77],"plane":[78],"to":[79,94,119,141,187,198,227,240],"spatial":[81],"spectral":[83],"localization.":[84],"We":[85,138],"introduce":[86],"separate":[87],"channels":[88],"capturing":[89],"low-":[90],"high-frequency":[92],"components":[93],"enhance":[95],"representation":[97],"while":[98,109,132],"maintaining":[99],"efficiency.":[100],"The":[101,166],"approach":[102],"reduces":[103],"trainable":[104],"parameters":[105,135],"training":[107,162],"time":[108],"preserving":[110],"accuracy,":[111],"making":[112],"it":[113,140],"suitable":[114],"resource-constrained":[116],"environments.":[117],"Compared":[118],"MobileNetV2":[120],"EfficientNetB0,":[122],"our":[123],"trains":[125],"approximately":[126],"4\u20136":[127],"\u00d7":[128,200,206],"faster":[129,161,201,207],"on":[130,215],"average":[131],"using":[133],"fewer":[134],"FLOPs.":[137],"compare":[139],"pretrained":[142],"used":[144],"as":[145],"extractors,":[147],"lightweight":[148],"fine-tuned":[149],"models,":[150],"classical":[152],"descriptors":[153],"(HOG,":[154],"LBP).":[155],"It":[156],"achieves":[157],"competitive":[158],"results":[159],"reduced":[164],"computation.":[165],"uses":[169],"only":[170],"around":[171],"0.60":[172],"GFLOPs":[173],"0.34":[175],"M":[176],"parameters,":[177],"we":[179],"apply":[180],"statistical":[181],"significance":[182],"testing":[183],"(ANOVA,":[184],"paired":[185],"t-tests)":[186],"validate":[188],"performance":[189],"gains.":[190],"Inference":[191],"takes":[192],"0.01\u20130.02":[193],"s":[194],"per":[195],"image,":[196],"up":[197],"15":[199],"than":[202,208],"EfficientNetB0":[203],"8":[205],"MobileNetV2.":[209],"Grad-CAM":[210],"visualizations":[211],"confirm":[212],"localized":[213],"attention":[214],"relevant":[216],"regions.":[217],"work":[219,234],"highlights":[220],"traditional":[222],"deep":[225],"improve":[228],"resource-limited":[231],"applications.":[232],"Future":[233],"will":[235],"address":[236],"color":[237],"fusion,":[238],"robustness":[239],"noise,":[241],"automated":[243],"optimization.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-01-05T00:00:00"}
