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Feature learning and process monitoring of injection molding using convolution-deconvolution auto encoders.

, , , , , and . Comput. Chem. Eng., (2018)

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Research on the Integration of GIS-Based Digital Valley System., , , and . IMSCCS (1), page 452-457. IEEE Computer Society, (2006)Intelligent setting of process parameters for injection molding based on case-based reasoning of molding features., , , , , , , and . J. Intell. Manuf., 33 (1): 77-89 (2022)Three-Dimensional Numerical Simulation of the Pressing Process in TV Panel Production., , and . Simulation, 82 (3): 193-203 (2006)Dimensional precision simulation of the formed picture tube panel., , , and . Eng. Comput. (Lond.), 25 (2): 165-177 (2009)Data driven injection molding process monitoring using sparse auto encoder technique., , , , , and . AIM, page 524-528. IEEE, (2015)Feature learning and process monitoring of injection molding using convolution-deconvolution auto encoders., , , , , and . Comput. Chem. Eng., (2018)Three-dimensional finite element method for the filling simulation of injection molding., , and . Eng. Comput. (Lond.), 21 (4): 289-295 (2006)Machining vibration states monitoring based on image representation using convolutional neural networks., , , , , , and . Eng. Appl. of AI, (2017)Automatic feature constructing from vibration signals for machining state monitoring., , , , , , and . J. Intelligent Manufacturing, 30 (3): 995-1008 (2019)A fractional-step thermal lattice Boltzmann model for high Peclet number flow., , , , and . Computers & Mathematics with Applications, 70 (5): 1152-1161 (2015)