{"id":"https://openalex.org/W4411016006","doi":"https://doi.org/10.1145/3728725.3728780","title":"Metal Level Measurement and Compensation Based on the MiDas Model","display_name":"Metal Level Measurement and Compensation Based on the MiDas Model","publication_year":2025,"publication_date":"2025-02-21","ids":{"openalex":"https://openalex.org/W4411016006","doi":"https://doi.org/10.1145/3728725.3728780"},"language":"en","primary_location":{"id":"doi:10.1145/3728725.3728780","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728780","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728780","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728780","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104363115","display_name":"Zhenyang Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I67001856","display_name":"Shanghai Institute of Technology","ror":"https://ror.org/00fjzqj15","country_code":"CN","type":"education","lineage":["https://openalex.org/I67001856"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenyang Lin","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0008-6493-5127","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai, China","institution_ids":["https://openalex.org/I67001856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5104363115"],"corresponding_institution_ids":["https://openalex.org/I67001856"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16582425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"342","last_page":"346"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9962000250816345,"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"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9962000250816345,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9746999740600586,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9735999703407288,"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/compensation","display_name":"Compensation (psychology)","score":0.6280294060707092},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3743894398212433},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07325807213783264}],"concepts":[{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.6280294060707092},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3743894398212433},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07325807213783264},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3728725.3728780","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728780","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728780","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3728725.3728780","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728780","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728780","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411016006.pdf","grobid_xml":"https://content.openalex.org/works/W4411016006.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W2171740948","https://openalex.org/W2354576866","https://openalex.org/W2798373498","https://openalex.org/W2941202065","https://openalex.org/W2955639361","https://openalex.org/W2962741876","https://openalex.org/W2963760790","https://openalex.org/W2963825193","https://openalex.org/W3035289617","https://openalex.org/W3081167590","https://openalex.org/W3101424466","https://openalex.org/W3207743087","https://openalex.org/W4225771998","https://openalex.org/W4285803579","https://openalex.org/W4307896876","https://openalex.org/W6703405610","https://openalex.org/W6752497527","https://openalex.org/W6841791177"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Accurate":[0],"measurement":[1,21,58,157],"of":[2,13,76,121,141,151],"liquid":[3,78,108,123,142],"metal":[4,79,109,143],"levels":[5],"is":[6,126],"critical":[7],"to":[8,39],"the":[9,42,103,107,122,139,148],"safety":[10,34],"and":[11,17,29,44,112,118,158],"efficiency":[12],"industrial":[14,87,155],"process":[15],"monitoring":[16,120],"automation.":[18],"Traditional":[19],"contact-based":[20],"methods":[22],"face":[23],"significant":[24],"limitations":[25],"in":[26,85,154],"high":[27],"temperature":[28],"extreme":[30],"environments,":[31],"such":[32],"as":[33],"risks,":[35],"inaccurate":[36],"measurements":[37],"due":[38],"interference":[40],"with":[41],"environment,":[43],"short":[45],"equipment":[46],"life.":[47],"To":[48],"address":[49],"these":[50,99],"challenges,":[51],"this":[52],"study":[53,129],"proposes":[54],"an":[55,74,86],"innovative":[56],"non-contact":[57,135],"method":[59],"using":[60],"a":[61,77,82,113,133],"visual":[62],"depth":[63,96,159],"estimation":[64],"technique":[65],"based":[66],"on":[67],"deep":[68,90,152],"learning.":[69],"The":[70],"MiDaS":[71],"model":[72],"captures":[73],"image":[75],"surface":[80],"by":[81,97],"monocular":[83],"camera":[84],"environment.":[88],"A":[89],"neural":[91],"network":[92],"then":[93],"estimates":[94],"their":[95],"processing":[98],"images.":[100],"By":[101],"calculating":[102],"vertical":[104],"distance":[105],"between":[106],"level":[110,124],"point":[111],"predefined":[114],"reference":[115],"point,":[116],"real-time":[117],"accurate":[119],"height":[125,140],"realized.":[127],"This":[128],"not":[130],"only":[131],"introduces":[132],"new":[134],"solution":[136],"for":[137],"measuring":[138],"surfaces,":[144],"but":[145],"also":[146],"enhances":[147],"potential":[149],"applications":[150],"learning":[153],"vision":[156],"estimation.":[160]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
