Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387675796> ?p ?o ?g. }
Showing items 1 to 90 of
90
with 100 items per page.
- W4387675796 endingPage "113672" @default.
- W4387675796 startingPage "113672" @default.
- W4387675796 abstract "Froth velocity is a crucial variable in froth flotation and its accurate detection is vital to process control. The velocity extraction is a challenging work under large throughput conditions due to the complex motion of the froth. Therefore, in this paper, a novel method called composite deep learning network (CDLN) is proposed, which is mainly composed by a cascade of pre-trained supervised network and an unsupervised network. The supervised network is pre-trained on a benchmark dataset and then is used to extract an initial flow field of the froth motion. The unsupervised network is trained on industrial froth videos with occlusion modeling to get a calibration flow field. The two flow fields are then fused to obtain the final flow field. The test results show that the proposed method can extract the froth velocity more accurately and faster than other popular methods through industrial froth videos under large throughput." @default.
- W4387675796 created "2023-10-17" @default.
- W4387675796 creator A5017083545 @default.
- W4387675796 creator A5049692788 @default.
- W4387675796 creator A5071328742 @default.
- W4387675796 creator A5083752100 @default.
- W4387675796 date "2023-10-01" @default.
- W4387675796 modified "2023-10-17" @default.
- W4387675796 title "Froth velocity extraction method from froth image for flotation with large throughput based on composite deep learning network" @default.
- W4387675796 cites W1525047497 @default.
- W4387675796 cites W1578285471 @default.
- W4387675796 cites W2042296747 @default.
- W4387675796 cites W2050625677 @default.
- W4387675796 cites W2085261163 @default.
- W4387675796 cites W2269094482 @default.
- W4387675796 cites W2560474170 @default.
- W4387675796 cites W2755756378 @default.
- W4387675796 cites W2765598240 @default.
- W4387675796 cites W2891590469 @default.
- W4387675796 cites W2912634210 @default.
- W4387675796 cites W2962864875 @default.
- W4387675796 cites W2963317244 @default.
- W4387675796 cites W2963782415 @default.
- W4387675796 cites W2964140947 @default.
- W4387675796 cites W2966108228 @default.
- W4387675796 cites W3005233762 @default.
- W4387675796 cites W3100018800 @default.
- W4387675796 cites W3104164805 @default.
- W4387675796 cites W3127140219 @default.
- W4387675796 cites W3176336346 @default.
- W4387675796 cites W3189424026 @default.
- W4387675796 cites W3214396588 @default.
- W4387675796 cites W4295836050 @default.
- W4387675796 cites W4385856497 @default.
- W4387675796 cites W764651262 @default.
- W4387675796 doi "https://doi.org/10.1016/j.measurement.2023.113672" @default.
- W4387675796 hasPublicationYear "2023" @default.
- W4387675796 type Work @default.
- W4387675796 citedByCount "0" @default.
- W4387675796 crossrefType "journal-article" @default.
- W4387675796 hasAuthorship W4387675796A5017083545 @default.
- W4387675796 hasAuthorship W4387675796A5049692788 @default.
- W4387675796 hasAuthorship W4387675796A5071328742 @default.
- W4387675796 hasAuthorship W4387675796A5083752100 @default.
- W4387675796 hasConcept C127313418 @default.
- W4387675796 hasConcept C127413603 @default.
- W4387675796 hasConcept C13280743 @default.
- W4387675796 hasConcept C154945302 @default.
- W4387675796 hasConcept C157764524 @default.
- W4387675796 hasConcept C185798385 @default.
- W4387675796 hasConcept C202444582 @default.
- W4387675796 hasConcept C21880701 @default.
- W4387675796 hasConcept C31972630 @default.
- W4387675796 hasConcept C33923547 @default.
- W4387675796 hasConcept C41008148 @default.
- W4387675796 hasConcept C555944384 @default.
- W4387675796 hasConcept C76155785 @default.
- W4387675796 hasConcept C9652623 @default.
- W4387675796 hasConceptScore W4387675796C127313418 @default.
- W4387675796 hasConceptScore W4387675796C127413603 @default.
- W4387675796 hasConceptScore W4387675796C13280743 @default.
- W4387675796 hasConceptScore W4387675796C154945302 @default.
- W4387675796 hasConceptScore W4387675796C157764524 @default.
- W4387675796 hasConceptScore W4387675796C185798385 @default.
- W4387675796 hasConceptScore W4387675796C202444582 @default.
- W4387675796 hasConceptScore W4387675796C21880701 @default.
- W4387675796 hasConceptScore W4387675796C31972630 @default.
- W4387675796 hasConceptScore W4387675796C33923547 @default.
- W4387675796 hasConceptScore W4387675796C41008148 @default.
- W4387675796 hasConceptScore W4387675796C555944384 @default.
- W4387675796 hasConceptScore W4387675796C76155785 @default.
- W4387675796 hasConceptScore W4387675796C9652623 @default.
- W4387675796 hasLocation W43876757961 @default.
- W4387675796 hasOpenAccess W4387675796 @default.
- W4387675796 hasPrimaryLocation W43876757961 @default.
- W4387675796 hasRelatedWork W2028665553 @default.
- W4387675796 hasRelatedWork W2086519370 @default.
- W4387675796 hasRelatedWork W2087343574 @default.
- W4387675796 hasRelatedWork W2105860728 @default.
- W4387675796 hasRelatedWork W2130974462 @default.
- W4387675796 hasRelatedWork W2378211422 @default.
- W4387675796 hasRelatedWork W2535915176 @default.
- W4387675796 hasRelatedWork W4287657826 @default.
- W4387675796 hasRelatedWork W4321353415 @default.
- W4387675796 hasRelatedWork W972276598 @default.
- W4387675796 isParatext "false" @default.
- W4387675796 isRetracted "false" @default.
- W4387675796 workType "article" @default.