{"id":"https://openalex.org/W7126040372","doi":"https://doi.org/10.1109/bibm66473.2025.11356042","title":"CMDFE: A Robust Few-Shot Learning Framework with Tiny Object Feature Extraction for Environmental Microorganism Image Classification","display_name":"CMDFE: A Robust Few-Shot Learning Framework with Tiny Object Feature Extraction for Environmental Microorganism Image Classification","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126040372","doi":"https://doi.org/10.1109/bibm66473.2025.11356042"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5037553960","display_name":"Xiangwen Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangwen Kong","raw_affiliation_strings":["Northeastern University,MIaMIA Group,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,MIaMIA Group,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101911266","display_name":"Tao Jiang","orcid":"https://orcid.org/0000-0003-3833-4498"},"institutions":[{"id":"https://openalex.org/I53411278","display_name":"Chengdu University of Traditional Chinese Medicine","ror":"https://ror.org/00pcrz470","country_code":"CN","type":"education","lineage":["https://openalex.org/I53411278"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Jiang","raw_affiliation_strings":["Chengdu University of Traditional Chinese Medicine,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chengdu University of Traditional Chinese Medicine,Chengdu,China","institution_ids":["https://openalex.org/I53411278"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124190750","display_name":"Hao Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hao Xu","raw_affiliation_strings":["University of Sydney,Sydney,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Sydney,Sydney,Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103655788","display_name":"Li Yuan","orcid":"https://orcid.org/0009-0007-0129-7669"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingling Yuan","raw_affiliation_strings":["Northeastern University,MIaMIA Group,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,MIaMIA Group,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124256873","display_name":"Marcin Grzegorzek","orcid":null},"institutions":[{"id":"https://openalex.org/I2802859012","display_name":"Becker College","ror":"https://ror.org/00vn6kg36","country_code":"US","type":"education","lineage":["https://openalex.org/I2802859012"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marcin Grzegorzek","raw_affiliation_strings":["University of L&#x00FC;beck,L&#x00FC;beck,German"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of L&#x00FC;beck,L&#x00FC;beck,German","institution_ids":["https://openalex.org/I2802859012"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124189671","display_name":"Rui Li","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Li","raw_affiliation_strings":["Northeastern University,MIaMIA Group,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,MIaMIA Group,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124197153","display_name":"Chen Li","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Li","raw_affiliation_strings":["Northeastern University,MIaMIA Group,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,MIaMIA Group,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5853","last_page":"5860"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.37599998712539673,"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":0.37599998712539673,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.3709999918937683,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.04580000042915344,"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/feature-extraction","display_name":"Feature extraction","score":0.6340000033378601},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5394999980926514},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5392000079154968},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49140000343322754},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4586000144481659},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4544000029563904},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4542999863624573},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.450300008058548}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7085000276565552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6754999756813049},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6340000033378601},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5394999980926514},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5392000079154968},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5009999871253967},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49140000343322754},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4586000144481659},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4544000029563904},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4542999863624573},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.450300008058548},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4259999990463257},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41749998927116394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4032000005245209},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.37389999628067017},{"id":"https://openalex.org/C2909468537","wikidata":"https://www.wikidata.org/wiki/Q58734","display_name":"Environmental pollution","level":2,"score":0.3702999949455261},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3598000109195709},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3499999940395355},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.34060001373291016},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C176585087","wikidata":"https://www.wikidata.org/wiki/Q864438","display_name":"Bioindicator","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2970193089","display_name":null,"funder_award_id":"82220108007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2067906210","https://openalex.org/W2110375261","https://openalex.org/W2146331300","https://openalex.org/W2467496703","https://openalex.org/W2565639579","https://openalex.org/W2761346076","https://openalex.org/W2808662277","https://openalex.org/W2944029760","https://openalex.org/W2951353256","https://openalex.org/W2984323660","https://openalex.org/W3107345204","https://openalex.org/W3131937156","https://openalex.org/W3202188231","https://openalex.org/W4245677428","https://openalex.org/W4286907180","https://openalex.org/W4313397847","https://openalex.org/W4319163914","https://openalex.org/W4386075985"],"related_works":[],"abstract_inverted_index":{"Environmental":[0],"Microorganisms":[1],"(EMs)":[2],"serve":[3],"as":[4],"vital":[5],"bioindicators":[6],"for":[7,33,144,157,164],"monitoring":[8,167],"environmental":[9,166],"pollution":[10],"monitoring.":[11],"However,":[12],"their":[13],"classification":[14,160],"is":[15,31],"challenged":[16],"by":[17],"severe":[18],"class":[19],"imbalance":[20],"and":[21,51,85,95,120,154,161],"a":[22,59,75,90,152],"lack":[23],"of":[24,29,107],"labeled":[25],"data.":[26],"Precise":[27],"identification":[28],"EMs":[30],"essential":[32],"timely":[34],"ecological":[35],"risk":[36],"assessment,":[37],"yet":[38],"conventional":[39],"methods":[40],"struggle":[41],"in":[42,118,128,146],"few-shot":[43,158],"learning":[44],"(FSL)":[45],"contexts":[46],"due":[47],"to":[48],"poor":[49],"generalization":[50],"overfitting.":[52],"To":[53],"overcome":[54],"these":[55],"challenges,":[56],"we":[57],"introduce":[58],"novel":[60],"Cross-stage":[61],"Multi-branch":[62],"Deep":[63],"Feature":[64],"Extraction":[65],"(CMDFE)":[66],"framework,":[67],"which":[68],"integrates":[69],"deep":[70],"feature":[71,83],"extraction":[72],"(Re)":[73],"with":[74],"lightweight":[76],"multi-branch":[77],"module":[78],"(C2f).":[79],"This":[80],"design":[81],"improves":[82],"diversity":[84],"mitigates":[86],"overfitting,":[87],"while":[88],"maintaining":[89],"favorable":[91],"balance":[92],"between":[93],"accuracy":[94,117],"computational":[96],"efficiency.":[97],"Experimental":[98],"results":[99],"on":[100],"the":[101,105],"EMDs7":[102],"dataset":[103],"demonstrate":[104],"effectiveness":[106],"CMDFE,":[108],"achieving":[109],"<tex":[110,121],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[111,122],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{6":[112],"8.":[113],"4":[114],"0":[115,125,126],"\\%}$</tex>":[116,127],"1-shot":[119],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{7":[123],"7.":[124],"5-shot":[129],"tasks,":[130],"surpassing":[131],"most":[132],"baseline":[133],"methods.":[134],"Additionally,":[135],"CMDFE":[136,150],"significantly":[137],"reduces":[138],"memory":[139],"usage,":[140],"making":[141],"it":[142],"well-suited":[143],"deployment":[145],"resource-constrained":[147],"environments.":[148],"Overall,":[149],"offers":[151],"robust":[153],"scalable":[155],"approach":[156],"EM":[159],"holds":[162],"promise":[163],"intelligent":[165],"applications.":[168]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-30T00:00:00"}
