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| Neural Network Model Combination Algorithm Based on Probability Optimization |
| LI Yana, LI Xian, YANG Mingyea, SUN Guoqinga
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| a. Department of automation;b. Institude For Future, Qingdao University, Qindao 266071, China |
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Abstract The high storage and computing cost limits the application of neural network model in low computing power platform. To overcome the above shortages, we proposed two combined probability optimization algorithms to combine multiple light neural networks in a continuous time window, which can significantly reduce computing load under similar accuracy. The proposed scheme gives a general way for related algorithm on embedded hardware. To verify its effectiveness, a group of experiment was executed on the pain expression recognition with continuous peak values. In comparison to other conventional algorithms, the model complexity, computing load and storage of proposed scheme decrease obviously under consistent accuracy.
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Received: 01 April 2021
Published: 12 October 2022
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