{"id":"https://openalex.org/W4416252340","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228149","title":"DRIP: DRop unImportant data Points - Enhancing Machine Learning Efficiency with Grad-CAM-Based Streaming Data Prioritization for On-Device Training","display_name":"DRIP: DRop unImportant data Points - Enhancing Machine Learning Efficiency with Grad-CAM-Based Streaming Data Prioritization for On-Device Training","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416252340","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228149"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5113373690","display_name":"Marcus R\u00fcb","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119362","display_name":"Hahn-Schickard-Gesellschaft f\u00fcr angewandte Forschung","ror":"https://ror.org/02reezy47","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I4210119362"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Marcus R\u00fcb","raw_affiliation_strings":["Hahn-Schickard,Villingen-Schwenningen,Germany"],"affiliations":[{"raw_affiliation_string":"Hahn-Schickard,Villingen-Schwenningen,Germany","institution_ids":["https://openalex.org/I4210119362"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120558034","display_name":"Daniel Konegen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119362","display_name":"Hahn-Schickard-Gesellschaft f\u00fcr angewandte Forschung","ror":"https://ror.org/02reezy47","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I4210119362"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Konegen","raw_affiliation_strings":["Hahn-Schickard,Villingen-Schwenningen,Germany"],"affiliations":[{"raw_affiliation_string":"Hahn-Schickard,Villingen-Schwenningen,Germany","institution_ids":["https://openalex.org/I4210119362"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106930220","display_name":"Axel Sikora","orcid":null},"institutions":[{"id":"https://openalex.org/I913140155","display_name":"Offenburg University of Applied Sciences","ror":"https://ror.org/03zh5eq96","country_code":"DE","type":"education","lineage":["https://openalex.org/I913140155"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Axel Sikora","raw_affiliation_strings":["Offenburg University,Offenburg,Germany"],"affiliations":[{"raw_affiliation_string":"Offenburg University,Offenburg,Germany","institution_ids":["https://openalex.org/I913140155"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011419637","display_name":"Daniel Mueller-Gritschneder","orcid":"https://orcid.org/0000-0003-0903-631X"},"institutions":[{"id":"https://openalex.org/I4210145666","display_name":"Embedded Systems (United States)","ror":"https://ror.org/04742eh45","country_code":"US","type":"company","lineage":["https://openalex.org/I4210145666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Mueller-Gritschneder","raw_affiliation_strings":["Embedded Computing Systems Faculty of Informatics, TU Wien,Vienna,Austria"],"affiliations":[{"raw_affiliation_string":"Embedded Computing Systems Faculty of Informatics, TU Wien,Vienna,Austria","institution_ids":["https://openalex.org/I4210145666"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5113373690"],"corresponding_institution_ids":["https://openalex.org/I4210119362"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37604927,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.511900007724762,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.511900007724762,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.15309999883174896,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.0333000011742115,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6039999723434448},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5437999963760376},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5360999703407288},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.526199996471405},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5011000037193298},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4993000030517578},{"id":"https://openalex.org/keywords/prioritization","display_name":"Prioritization","score":0.4973999857902527},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.45590001344680786}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7774999737739563},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6434000134468079},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6039999723434448},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5437999963760376},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5360999703407288},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.526199996471405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5090000033378601},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5011000037193298},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4993000030517578},{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.4973999857902527},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49320000410079956},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.45590001344680786},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4187000095844269},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4065000116825104},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.36660000681877136},{"id":"https://openalex.org/C2777851325","wikidata":"https://www.wikidata.org/wiki/Q7094102","display_name":"Online model","level":2,"score":0.3483999967575073},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.3377000093460083},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.32350000739097595},{"id":"https://openalex.org/C197298091","wikidata":"https://www.wikidata.org/wiki/Q5318963","display_name":"Dynamic data","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C2779466056","wikidata":"https://www.wikidata.org/wiki/Q107630651","display_name":"Time point","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.hs-offenburg.de:12065","is_oa":false,"landing_page_url":"https://opus.hs-offenburg.de/frontdoor/index/index/docId/12065","pdf_url":null,"source":{"id":"https://openalex.org/S4377196587","display_name":"Opus-HSO (Offenburg University of Applied Sciences)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I913140155","host_organization_name":"Offenburg University of Applied Sciences","host_organization_lineage":["https://openalex.org/I913140155"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"doc-type:conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2108572107","https://openalex.org/W2129888542","https://openalex.org/W2293587938","https://openalex.org/W2962858109","https://openalex.org/W2964817253","https://openalex.org/W3116196021","https://openalex.org/W4224316937","https://openalex.org/W4283023598","https://openalex.org/W4283205568","https://openalex.org/W4283796010","https://openalex.org/W4285602083","https://openalex.org/W4286355545","https://openalex.org/W4372260579","https://openalex.org/W4391248980","https://openalex.org/W4399555049","https://openalex.org/W4401880730","https://openalex.org/W4402352532"],"related_works":[],"abstract_inverted_index":{"Selecting":[0],"data":[1,27,51,70,79,138],"points":[2],"for":[3,22,54,84],"model":[4,32,91],"training":[5,21],"is":[6,129],"critical":[7],"in":[8],"machine":[9],"learning.":[10],"Effective":[11],"selection":[12],"methods":[13],"can":[14,103],"reduce":[15],"the":[16,31,57,66,108,114,130,145],"labeling":[17],"effort,":[18],"optimize":[19],"on-device":[20],"embedded":[23,55],"systems":[24],"with":[25],"limited":[26],"storage,":[28],"and":[29],"enhance":[30],"performance.":[33,92],"This":[34,72],"paper":[35],"introduces":[36],"a":[37,60,78],"novel":[38],"algorithm":[39,58,132],"that":[40,100],"uses":[41],"Grad-CAM":[42],"to":[43,64,123,133,144],"make":[44,134],"online":[45,135],"decisions":[46,136],"about":[47,137],"retaining":[48],"or":[49,87,105],"discarding":[50],"points.":[52],"Optimized":[53],"devices,":[56],"computes":[59],"unique":[61],"DRIP":[62],"Score":[63],"quantify":[65],"importance":[67],"of":[68,110,121],"each":[69],"point.":[71],"enables":[73],"dynamic":[74],"decision-making":[75],"on":[76,95,113],"whether":[77],"point":[80,139],"should":[81],"be":[82],"stored":[83],"potential":[85],"retraining":[86],"discarded":[88],"without":[89,141],"compromising":[90],"Experimental":[93],"evaluations":[94],"four":[96],"benchmark":[97],"datasets":[98],"demonstrate":[99],"our":[101,126],"approach":[102],"match":[104],"even":[106],"surpass":[107],"accuracy":[109],"models":[111],"trained":[112],"entire":[115,146],"dataset,":[116],"while":[117],"achieving":[118],"storage":[119],"savings":[120],"up":[122],"39%.":[124],"To":[125],"knowledge,":[127],"this":[128],"first":[131],"retention":[140],"requiring":[142],"access":[143],"dataset.":[147]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}
