{"id":"https://openalex.org/W4401164342","doi":"https://doi.org/10.1109/eit60633.2024.10609939","title":"A PyTorch-Based Deep Learning Approach for Enhanced Liquid Level Detection in Industrial Environments","display_name":"A PyTorch-Based Deep Learning Approach for Enhanced Liquid Level Detection in Industrial Environments","publication_year":2024,"publication_date":"2024-05-30","ids":{"openalex":"https://openalex.org/W4401164342","doi":"https://doi.org/10.1109/eit60633.2024.10609939"},"language":"en","primary_location":{"id":"doi:10.1109/eit60633.2024.10609939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eit60633.2024.10609939","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Electro Information Technology (eIT)","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/A5062167058","display_name":"Abhinav Narayan","orcid":null},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abhinav Narayan","raw_affiliation_strings":["Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,IL,USA"],"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,IL,USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006049924","display_name":"Deanne Charan","orcid":null},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charan D K","raw_affiliation_strings":["Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,IL,USA"],"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,IL,USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106211452","display_name":"Sneha Elizabeth Saji","orcid":null},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sneha Elizabeth Saji","raw_affiliation_strings":["Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,IL,USA"],"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,IL,USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074654866","display_name":"Tianyang Fang","orcid":"https://orcid.org/0009-0007-8741-0473"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianyang Fang","raw_affiliation_strings":["Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,IL,USA"],"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,IL,USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018536803","display_name":"Jafar Saniie","orcid":"https://orcid.org/0000-0002-2655-6950"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jafar Saniie","raw_affiliation_strings":["Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,IL,USA"],"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,IL,USA","institution_ids":["https://openalex.org/I180949307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5062167058"],"corresponding_institution_ids":["https://openalex.org/I180949307"],"apc_list":null,"apc_paid":null,"fwci":1.1586,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.81132534,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"562","last_page":"566"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.628600001335144,"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"}},"topics":[{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.628600001335144,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.569599986076355,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.5612000226974487,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/deep-learning","display_name":"Deep learning","score":0.7293320894241333},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7135132551193237},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5820741653442383},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3438517153263092}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7293320894241333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7135132551193237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5820741653442383},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3438517153263092}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eit60633.2024.10609939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eit60633.2024.10609939","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Electro Information Technology (eIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2194775991","https://openalex.org/W2523246573","https://openalex.org/W2803187616","https://openalex.org/W2913687414","https://openalex.org/W2963446712","https://openalex.org/W2996621571","https://openalex.org/W3042556523","https://openalex.org/W4366572742","https://openalex.org/W4387375163","https://openalex.org/W6637373629","https://openalex.org/W6727249380","https://openalex.org/W6751420435"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3046775127","https://openalex.org/W3082895349"],"abstract_inverted_index":{"The":[0],"accurate":[1],"detection":[2,120],"of":[3,7,46,76,118],"liquid":[4,20],"levels":[5,21],"is":[6,51],"paramount":[8],"importance":[9],"across":[10,121],"various":[11],"industries,":[12],"including":[13],"pharmaceuticals,":[14],"beverages,":[15],"and":[16,40,64,116],"chemicals.":[17],"Traditionally,":[18],"monitoring":[19],"within":[22],"containers":[23],"has":[24],"relied":[25],"on":[26],"manual":[27],"procedures":[28],"or":[29],"basic":[30],"sensor":[31],"technology,":[32],"which":[33],"often":[34],"encounters":[35],"challenges":[36],"related":[37],"to":[38,60,84,99,110],"precision":[39],"speed.":[41],"However,":[42],"as":[43],"the":[44,74,86,113],"field":[45],"computer":[47,96],"vision":[48,97],"advances,":[49],"there":[50],"a":[52,78],"growing":[53],"interest":[54],"in":[55],"leveraging":[56],"more":[57],"advanced":[58,100],"techniques":[59,103],"overcome":[61],"these":[62],"limitations":[63],"enhance":[65],"liquid-level":[66,90,119],"monitoring.":[67,91],"In":[68],"this":[69,71,107],"context,":[70],"research":[72],"proposes":[73],"utilization":[75],"PyTorch,":[77,106],"powerful":[79],"open-source":[80],"deep":[81,101],"learning":[82,102],"framework,":[83],"tackle":[85],"intricacies":[87],"associated":[88],"with":[89],"By":[92],"transitioning":[93],"from":[94],"traditional":[95],"methods":[98],"facilitated":[104],"by":[105],"study":[108],"aims":[109],"significantly":[111],"improve":[112],"accuracy,":[114],"efficiency,":[115],"reliability":[117],"industrial":[122],"applications.":[123]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}
