{"id":"https://openalex.org/W7154725341","doi":"https://doi.org/10.1109/lats70329.2026.11480323","title":"Convolutional Neural Networks for Energy Estimation in High-Energy Calorimetry","display_name":"Convolutional Neural Networks for Energy Estimation in High-Energy Calorimetry","publication_year":2026,"publication_date":"2026-03-17","ids":{"openalex":"https://openalex.org/W7154725341","doi":"https://doi.org/10.1109/lats70329.2026.11480323"},"language":null,"primary_location":{"id":"doi:10.1109/lats70329.2026.11480323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lats70329.2026.11480323","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 27th Latin American Test Symposium (LATS)","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/A5122201227","display_name":"Diogo Alves Cardinot","orcid":null},"institutions":[{"id":"https://openalex.org/I40034438","display_name":"Universidade do Estado do Rio de Janeiro","ror":"https://ror.org/0198v2949","country_code":"BR","type":"education","lineage":["https://openalex.org/I40034438"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Diogo Alves Cardinot","raw_affiliation_strings":["Graduate Program in Computational Modeling Rio de Janeiro State University,Nova Friburgo,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Program in Computational Modeling Rio de Janeiro State University,Nova Friburgo,Brazil","institution_ids":["https://openalex.org/I40034438"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106575359","display_name":"B. S. Peralva","orcid":"https://orcid.org/0000-0003-1664-5658"},"institutions":[{"id":"https://openalex.org/I40034438","display_name":"Universidade do Estado do Rio de Janeiro","ror":"https://ror.org/0198v2949","country_code":"BR","type":"education","lineage":["https://openalex.org/I40034438"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Bernardo Sotto-Maior Peralva","raw_affiliation_strings":["Rio de Janeiro State University,Computational Modeling Department,Nova Friburgo,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rio de Janeiro State University,Computational Modeling Department,Nova Friburgo,Brazil","institution_ids":["https://openalex.org/I40034438"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088285399","display_name":"Gustavo Barbosa Libotte","orcid":"https://orcid.org/0000-0002-4583-6026"},"institutions":[{"id":"https://openalex.org/I40034438","display_name":"Universidade do Estado do Rio de Janeiro","ror":"https://ror.org/0198v2949","country_code":"BR","type":"education","lineage":["https://openalex.org/I40034438"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Gustavo Barbosa Libotte","raw_affiliation_strings":["Rio de Janeiro State University,Computational Modeling Department,Nova Friburgo,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rio de Janeiro State University,Computational Modeling Department,Nova Friburgo,Brazil","institution_ids":["https://openalex.org/I40034438"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5133871445","display_name":"Luciano de Manh\u00e3es Andrade Filho","orcid":null},"institutions":[{"id":"https://openalex.org/I101100930","display_name":"Universidade Federal de Juiz de Fora","ror":"https://ror.org/04yqw9c44","country_code":"BR","type":"education","lineage":["https://openalex.org/I101100930"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Luciano de Manh\u00e3es Andrade Filho","raw_affiliation_strings":["Federal University of Juiz de Fora,Electric Circuits Department,Juiz de Fora,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Juiz de Fora,Electric Circuits Department,Juiz de Fora,Brazil","institution_ids":["https://openalex.org/I101100930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.5285824,"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":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.2425999939441681,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.2425999939441681,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10048","display_name":"Particle physics theoretical and experimental studies","score":0.0738999992609024,"subfield":{"id":"https://openalex.org/subfields/3106","display_name":"Nuclear and High Energy Physics"},"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/T11176","display_name":"Radiation Therapy and Dosimetry","score":0.046300001442432404,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5321999788284302},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4465000033378601},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4406000077724457},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3617999851703644},{"id":"https://openalex.org/keywords/calorimetry","display_name":"Calorimetry","score":0.35989999771118164},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33640000224113464}],"concepts":[{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5321999788284302},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5264999866485596},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49399998784065247},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4465000033378601},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4406000077724457},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4212000072002411},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C202270520","wikidata":"https://www.wikidata.org/wiki/Q634314","display_name":"Calorimetry","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3230000138282776},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3100999891757965},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2784000039100647},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lats70329.2026.11480323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lats70329.2026.11480323","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 27th Latin American Test Symposium (LATS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8634774088859558}],"awards":[{"id":"https://openalex.org/G3004145990","display_name":null,"funder_award_id":"E-26/201.304/2022,E-26/210.430/2024","funder_id":"https://openalex.org/F4320322749","funder_display_name":"Funda\u00e7\u00e3o Carlos Chagas Filho de Amparo \u00e0 Pesquisa do Estado do Rio de Janeiro"},{"id":"https://openalex.org/G6085108940","display_name":null,"funder_award_id":"309784/2025-5","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320322749","display_name":"Funda\u00e7\u00e3o Carlos Chagas Filho de Amparo \u00e0 Pesquisa do Estado do Rio de Janeiro","ror":"https://ror.org/03kk0s825"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W597265994","https://openalex.org/W1964402708","https://openalex.org/W2002576046","https://openalex.org/W2022939780","https://openalex.org/W2027148138","https://openalex.org/W2058958287","https://openalex.org/W2122144238","https://openalex.org/W2128158076","https://openalex.org/W2939880928","https://openalex.org/W2963406555","https://openalex.org/W2995248424","https://openalex.org/W2998329591","https://openalex.org/W3025344913","https://openalex.org/W4214725106","https://openalex.org/W4234296777","https://openalex.org/W4293174100","https://openalex.org/W4318035786","https://openalex.org/W4411712954","https://openalex.org/W4416078327"],"related_works":[],"abstract_inverted_index":{"Particle":[0],"accelerators":[1],"are":[2,145],"complex":[3],"facilities":[4],"that":[5,34,69,100,143],"collide":[6],"particles":[7],"at":[8,13],"extreme":[9],"high":[10],"speed,":[11],"aiming":[12],"discovering":[14],"new":[15,42],"physics.":[16],"In":[17],"this":[18],"context,":[19],"high-energy":[20,78],"calorimeter":[21,149],"systems":[22],"plays":[23],"a":[24,128],"crucial":[25],"role":[26],"as":[27,156],"it":[28],"provides":[29],"the":[30,40,47,50,64,71,109,115,125,134,157],"particle":[31],"energy":[32,150],"quantity":[33],"is":[35,83],"an":[36],"important":[37],"information":[38],"for":[39,148,160],"potential":[41],"discoveries.":[43],"This":[44],"work":[45],"evaluates":[46],"performance":[48,106],"of":[49,66,95],"Optimal":[51],"Filter":[52],"(OF)":[53],"method":[54],"and":[55,93],"several":[56],"Convolutional":[57],"Neural":[58],"Network":[59],"(CNN)":[60],"architectures":[61,103],"in":[62,77,153],"reconstructing":[63],"amplitude":[65],"simulated":[67],"signals":[68],"represent":[70],"response":[72],"pulses":[73],"produced":[74],"by":[75],"calorimeters":[76],"physics":[79],"experiments.":[80,162],"The":[81,97],"comparison":[82],"conducted":[84],"using":[85],"quantitative":[86],"metrics":[87],"\u2014":[88],"including":[89],"RMS,":[90],"MAE,":[91],"MedAE,":[92],"Coefficient":[94],"Determination.":[96],"results":[98],"show":[99],"different":[101],"CNN":[102],"exhibit":[104],"varying":[105],"depending":[107],"on":[108],"occupancy":[110],"rate":[111],"but":[112],"generally":[113],"outperform":[114],"commonly":[116],"used":[117],"linear":[118],"method,":[119],"providing":[120],"more":[121],"accurate":[122],"reconstructions.":[123],"Although":[124],"proposed":[126],"requires":[127],"large":[129],"execution":[130],"time":[131],"due":[132],"to":[133],"training":[135],"process":[136],"across":[137],"multiple":[138],"folds,":[139],"these":[140],"findings":[141],"indicate":[142],"CNNs":[144],"promising":[146],"alternatives":[147],"reconstruction,":[151],"particularly":[152],"high-occupancy":[154],"conditions":[155],"ones":[158],"expected":[159],"high-luminosity":[161]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-18T00:00:00"}