{"id":"https://openalex.org/W7135019307","doi":"https://doi.org/10.48550/arxiv.2603.10782","title":"Phase-Interface Instance Segmentation as a Visual Sensor for Laboratory Process Monitoring","display_name":"Phase-Interface Instance Segmentation as a Visual Sensor for Laboratory Process Monitoring","publication_year":2026,"publication_date":"2026-03-11","ids":{"openalex":"https://openalex.org/W7135019307","doi":"https://doi.org/10.48550/arxiv.2603.10782"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.10782","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10782","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.10782","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128808721","display_name":"Mingyue Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Mingyue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128823330","display_name":"Xin Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128862872","display_name":"Shilin Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Shilin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128868891","display_name":"Jinye Ran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ran, Jinye","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120861918","display_name":"Morui Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Morui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066365017","display_name":"Zirui Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Zirui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128843084","display_name":"Huanqing Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Huanqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128900058","display_name":"Wei Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102012814","display_name":"Guanghua Zhang","orcid":"https://orcid.org/0000-0001-8804-4072"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Guanghua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128893675","display_name":"Shuo Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Shuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128815773","display_name":"Hao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":11,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.2639999985694885,"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":0.2639999985694885,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.07919999957084656,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.045499999076128006,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6718999743461609},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6276999711990356},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.569599986076355},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5479999780654907},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.531499981880188},{"id":"https://openalex.org/keywords/visual-inspection","display_name":"Visual inspection","score":0.43290001153945923},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.4318999946117401},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40700000524520874}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6718999743461609},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6707000136375427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6413000226020813},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6276999711990356},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.583299994468689},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.569599986076355},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5479999780654907},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.531499981880188},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.43290001153945923},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.4318999946117401},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40700000524520874},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.3935000002384186},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.38999998569488525},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3276999890804291},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C2778307483","wikidata":"https://www.wikidata.org/wiki/Q5149038","display_name":"Colored","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C37789001","wikidata":"https://www.wikidata.org/wiki/Q782543","display_name":"Graphical user interface","level":2,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.10782","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10782","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.10782","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10782","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reliable":[0],"visual":[1,161],"monitoring":[2,144],"of":[3,29,84],"chemical":[4],"experiments":[5],"remains":[6],"challenging":[7],"in":[8,145],"transparent":[9],"glassware,":[10],"where":[11],"weak":[12],"phase":[13,30,147],"boundaries":[14],"and":[15,32,51,75,97,107,136,149],"optical":[16],"artifacts":[17],"degrade":[18],"conventional":[19],"segmentation.":[20,59],"We":[21],"formulate":[22],"laboratory":[23,164],"phenomena":[24],"as":[25,129,158],"the":[26,34,91,102],"time":[27],"evolution":[28],"interfaces":[31],"introduce":[33],"Chemical":[35],"Transparent":[36],"Glasses":[37],"dataset":[38],"2.0":[39],"(CTG":[40],"2.0),":[41],"a":[42,76,159],"vessel-aware":[43],"benchmark":[44],"with":[45,133],"3,668":[46],"images,":[47],"23":[48],"glassware":[49],"categories,":[50],"five":[52],"multiphase":[53],"interface":[54],"types":[55],"for":[56,71,81,163],"phase-interface":[57,153],"instance":[58,154],"Building":[60],"on":[61],"YOLO11m-seg,":[62],"we":[63,140],"propose":[64],"LGA-RCM-YOLO,":[65],"which":[66],"combines":[67],"Local-Global":[68],"Attention":[69],"(LGA)":[70],"robust":[72],"semantic":[73],"representation":[74],"Rectangular":[77],"Self-Calibration":[78],"Module":[79],"(RCM)":[80],"boundary":[82],"refinement":[83],"thin,":[85],"elongated":[86],"interfaces.":[87],"On":[88],"CTG":[89],"2.0,":[90],"proposed":[92],"model":[93],"achieves":[94],"84.4%":[95],"AP@0.5":[96],"58.43%":[98],"AP@0.5-0.95,":[99],"improving":[100],"over":[101],"YOLO11m":[103],"baseline":[104],"by":[105],"6.42":[106],"8.75":[108],"AP":[109],"points,":[110],"respectively,":[111],"while":[112],"maintaining":[113],"near":[114],"real-time":[115],"inference":[116],"(13.67":[117],"FPS,":[118],"RTX":[119],"3060).":[120],"An":[121],"auxiliary":[122],"color-attribute":[123],"head":[124],"further":[125],"labels":[126],"liquid":[127],"instances":[128],"colored":[130],"or":[131],"colorless":[132],"98.71%":[134],"precision":[135],"98.32%":[137],"recall.":[138],"Finally,":[139],"demonstrate":[141],"continuous":[142],"process":[143],"separatory-funnel":[146],"separation":[148],"crystallization,":[150],"showing":[151],"that":[152],"segmentation":[155],"can":[156],"serve":[157],"practical":[160],"sensor":[162],"automation.":[165]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-13T00:00:00"}