2020
DOI: 10.1007/s11548-020-02120-3
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Lattice-Boltzmann interactive blood flow simulation pipeline

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Cited by 12 publications
(1 citation statement)
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“…In [9], multilayer perceptron (MLP) neural network was adopted to realize mapping between objective positions and positioning parameters in two-step method for indoor WiFi-based localization. However, deep neural networks often require a large number of fully connected relationships, which puts great pressure on real-time computation and pretraining of nodes, making it difficult to achieve the real-time superiority of advanced optimization methods as described in [10][11][12]. The scheme based on LSTM network is introduced in the context of ultra wide band (UWB) technology, whose relative positioning error can reach 1.4% [13], but the disadvantage is also high complexity.…”
mentioning
confidence: 99%
“…In [9], multilayer perceptron (MLP) neural network was adopted to realize mapping between objective positions and positioning parameters in two-step method for indoor WiFi-based localization. However, deep neural networks often require a large number of fully connected relationships, which puts great pressure on real-time computation and pretraining of nodes, making it difficult to achieve the real-time superiority of advanced optimization methods as described in [10][11][12]. The scheme based on LSTM network is introduced in the context of ultra wide band (UWB) technology, whose relative positioning error can reach 1.4% [13], but the disadvantage is also high complexity.…”
mentioning
confidence: 99%