In this paper, we present the depth-adaptive deep neural network using a depth map for semantic segmentation. Typical deep neural networks receive inputs at the predetermined locations regardless of the distance from the camera. This fixed receptive field presents a challenge to generalize the ...
Fig. 1. (A) A shallow (one hidden layer) and (B) a deep (multiple hidden layers) neural network. Various nonlinear functions have been proposed for approximation, pattern recognition, and classification problems. In MLP, the nodes in successive layers are connected and the connections are weig...
In recent years, deep learning has achieved great success in the field of image processing. In the single image super-resolution (SISR) task, the convolutional neural network (CNN) extracts the features of the image through deeper layers, and has achieved impressive results. In this paper, we ...
包含111个Point Deep Learning Models MANN.cs 120行,MonoBehaviour类,定义MANN的网络结构 PFNN.cs 95行,MonoBehaviour类,定义PFNN的网络结构 NeuralNetwork.cs 261行,MonoBehaviour类,相当于torch.nn.Module,MANN和PFNN继承自此类 Parameter.cs 96行,ScriptableObject类,存放权重数据的缓冲,从bin文件读入权重暂时存在这,...
Deep neural networks (DNNs) are vulnerable to adversarial examples that are similar to original samples but contain the perturbations intentionally crafted by adversaries. Many efficient and typical attacks are based on the fast gradient sign method and usually against models by adding invariant perturbat...
Accurate deep neural network inference using computational phase-change memory. Nat. Commun. 11, 1–13 (2020). Article ADS CAS Google Scholar Download references Acknowledgements Authors would like to thank Prof. Tuo-Hung Hou from NCTU, Taiwan for providing HfO2/TiO2 RRAM devices. PI: M.S. ...
The dynamic balance between the excitatory and inhibitory neurons accelerates the convergence of the neural networks and improves their performance. We use the combination of the two mechanisms to propose a deep SNN with adaptive self-feedback and balanced excitatory–inhibitory neurons (BackEISNN). ...
processes. A coupling between a conventional integrator and the ML regressor was attempted, and speed-up performances were analyzed. They also tried to infer the solution of Euler’s equations for a single one-dimensional reacting shock flow scenario by leveraging a deep neural network (DNN). Sc...
It aims to build a multi-layer network and extract complex features from raw input data to mine the hidden knowledge structures in the data. The training of deep neural networks requires representative datasets, which may contain private information of individuals such as clinical records, user ...
作者认为在许多场景下,用户选择了一个特定的target category作为全局的过滤器,然而现有的会话推荐方法只考虑项目的顺序信息,而忽视了丰富的target category information。为了解决这个问题,作者提出了Intention Adaptive Graph Neural Network (IAGNN)模型。 作者举个例子来说明了背景,以下图为例:...