Neuropower: Designing energy efficient convolutional neural network architecture for embedded systems. In Proceedings of the International Conference on Artificial Neural Networks, Munich, Germany, 17–19 September 2019; pp. 208–222. [Google Scholar] Liu, C.; Chen, L.C.; Schroff, F.; Adam, H...
Recurrent Neural Networks are one of the most common Neural Networks used in Natural Language Processing because of its promising results. The applications of RNN in language models consist of two main approaches. We can either make the model predict or
NAS: Neural architecture search, NAS Algorithms, Automated Neural Network Design, Architecture Search Space, Neural Network Optimization, Neural Network Architecture Optimization. • Feature engineering: Meta-learning. • Architecture Optimization: Evolutionary Algorithm, Reinforcement Learning, Bayesian Optimiz...
Layers in the deep learning model can be considered as the architecture of the model. There can be various types of layers that can be used in the models. All of these different layers have their own importance based on their features. Like we use LSTM layers mostly in the time series an...
Figure 3 illustrates the network architecture of the base U-Net. Figure 3 Base U-Net architecture. Full size image Attention U-Net The improved version of the base U-Net architecture was first introduced by Oktay et al. as attention U-Net in 201870. The attention U-Net architecture, Fig....
Pipeline of TAB for the pose estimation of multiple multi-joint fish-like robots and its detailed network architecture. TAB simultaneously outputs the detection and key points information of multiple fish-like robots using the parallel structure. View Figure 3 The network architecture of IOL for th...
To demonstrate the usefulness of transfer learning, we also perform the direct training of the 5 models with the same ensemble network architecture and hyperparameters (the number of layers, the depth of layers, the kernel size, the dilation factor, and the learning rate) on the structured RNA...
This integration method is composed of two identical adaptive noise cancellers using a linear neural network with just one bias weight. Its behavior has ... M Cirrincione,M Pucci,G Cirrincione,... - 《Power Electronics IEEE Transactions on》 被引量: 148发表: 2004年 Choosing a heuristic for...
This paper uses a simple yet compact network structure, a unique loss function, and a relatively flexible embedded attention module, which is more effective and easier to arrange in robotic platforms with weak arithmetic power. The tests show that our network structure not only shows high quality...
maker procedures (that compute the label vector of each pixel) were employed to ascertain noisy or noise-free color pixels. Sparse clean image replaced corrupted channels (0 for noise free). Finally, the denoised image was reconstructed by the image reconstruction architecture. In a nutshell, ...