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Method for performing adjustable continual learning on deep neural network model by using selective deep generative replay module and device using the same
Method for performing adjustable continual learning on deep neural network model by using selective deep generative replay module and device using the same
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机译:通过使用相同的选择性深度生成重放模块和设备在深神经网络模型上执行可调连续学习的方法
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摘要
A method of adjustable continual learning of a deep neural network model by using a selective deep generative replay module is provided. The method includes steps of: a learning device (a) (i) inputting training data from a total database and a sub-database into the selective deep generative replay module to generate first and second low-dimensional distribution features, (ii) inputting binary values, random parameters, and the second low-dimensional distribution features into a data generator to generate a third training data, and (iii) inputting a first training data into a solver to generate labeled training data; (b) inputting the training data, the low-dimensional distribution features, and the binary values into a discriminator to generate a first and a second training data scores, a first and a second feature distribution scores, and a third training data score; and (c) training the discriminator, the data generator, the distribution analyzer and the solver.
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