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Deep learning models are neural networks with more layers.
Deep learning models have recently gained attention by the researchers.
Deep Learning models have achieved remarkable results in speech recognition and computer vision in recent years.
Deep learning models become computationally inefficient with the increase in big data complexity.
Deep learning models are inherently computationally complex and require many-core CPUs and large-scale computational infrastructures.
Deep learning models are hierarchical representations of supervised and unsupervised classification methods that are best suitable for large-scale, high-dimensional big data streams [22].
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In their recent work [20], a deep learning model was used for F0 modeling in emotional VC.
Section 2 introduces relevant works, deep learning model.
Their Deep Learning model outperforms other existing approaches.
We develop a deep learning model to predict traffic flows.
In contrast to data mining, a Deep Learning model, learns features during the process of learning.
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