論文程式碼:https://paperswithcode.com/paper/dccrn-deep-complex-convolution-recurrent-1 引用:Hu Y,Liu Y,Lv S,et al. DCCRN: Deep complex convolution recurrent network for phase-aware speech enhancement[J]. arXiv preprint arXiv:2008.00264,2020. 摘要 語音增強得益於深度學習在可理解性和感知質量方面...
Over the past 10 years, advances in algorithms for deep learning and processing capability have led to the development of many efficient deep neural network-based lane detection techniques17,18. In certain algorithms, CNN was used as a method for extracting features to determine lane borders, and...
Since popular RNN components such as LSTM andgated recurrent unit(GRU) have already been implemented in most of the frameworks, users do not need to care about the underlying implementations. However, if you want to significantly modify them or make a completely new algorithm and components, the...
Learning complex spectral mapping with gated convolutional recurrent networks for monaural speech enhancement[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2019, 28: 380-390. 摘要 相位对于语音的感知质量很重要。 但是由于其中缺乏频谱时间结构,通过监督学习直接估计相位谱似乎很难。
More practically, the (higher-order) node features are propagated by the neural network when many layers are stacked: deeper the architecture, i.e., the more convolutional layers, the farther the features propagate, capturing the importance of the neighborhood of each node. Specifically, we stack...
Learning Complex Spectral Mapping with Gated Convolutional Recurrent Networks for Monaural Speech Enhancement This repository provides an implementation of the gated convolutional recurrent network (GCRN) for monaural speech enhancement, developed in"Learning complex spectral mapping with gated convolutional recurr...
[42] first used homomorphic encryption function in compressed sensing data collection, and proposed an efficient data collection method with privacy protection to prevent traffic analysis and tracking in wireless sensor networks. Liuet al. [43] propose a neural network algorithm of gated recurrent ...
deep learning for human activity recognition, we briefly reviewed the different deep learning methods for human activities implemented recently and then propose a conceptual deep learning frameworks that can be used to extract global features that model the temporal dependencies using Gated Recurrent Units...
The formation of the nervous system requires a balance between proliferation, differentiation, and migration of neural progenitors (NPs). Mutations in genes regulating development impede neurogenesis and lead to neuropsychiatric diseases, including autis
seen in dynamic imaging are 3D koosh-ball or stack-of-stars12,14,15which would result in streaking undersampling artifacts for which a different trained network would be probably required. Different architectural choices, such as 3D recurrent convolutional networks or variational neural networks,...