关键词: distributed processing feature extraction recurrent neural nets resource allocation time series wavelet transforms neural network based performance prediction recurrent networks resource utilization time series prediction 会议名称: 2006 IEEE International Conference on Engineering of Intelligent Systems 主办...
展开 关键词: electrical engineering computing learning (artificial intelligence microstrip antennas neural nets ANN antenna optimization electromagnetic optimization microstrip antennas multiple neural networks proximity coupled feed antenna 会议名称: 2014 International Joint Conference on Neural Networks (IJCNN) 主...
Results showed that variations in model parameters that have small variations on model predictions can have a large impact on the out-of-distribution detection performance. This kind of behavior needs to be addressed when DNNs are part of a safety critical application and hence, the necessary ...
There are two broad categories of ANNs based on the number of hidden layers:shallowanddeep neural networks. Shallow ANNs have only one hidden layer, while deep neural networks (DNNs or deep nets) have two or more hidden layers. There are also different types of neural network architectures. H...
convolutional neural netsimage segmentationMost self‐distillation methods need complex auxiliary teacher structures and require lots of training samples in object... L Chen,T Cao,Y Zheng,... - 《Iet Computer Vision》 被引量: 0发表: 2023年 Effective Model Compression via Stage-wise Pruning convolu...
It has been found that the performance of a hybrid subspace model for the kinetics of a typical processing operation is superior to that of an SBNN model for the entire predictor variable space. 展开 关键词: Sigmoidal backpropagation neural nets connectionist networks sparse data hybrid subspace ...
& Cao, W. On hidden nodes for neural nets. IEEE Trans. Circuits Syst. 36, 661–664 (1989). Article MathSciNet Google Scholar Huang, G.-B. Learning capability and storage capacity of two-hidden-layer feedforward networks. IEEE Trans. Neural Netw. 14, 274–281 (2003). Article Google...
Unfortunately, their method only works for neural nets having the same number of neurons in each hidden layer. Furthermore, they guarantee no invariance across residual connections. This is unlike neural teleportation, which works for any network architecture, including residual networks. Scale-...
Basic functions of all types of neural networks are data receipt from the external situation or sources, decide if this data will be activated and taken into account or is discarded as negligible, analysis or error minimization by iteration of the data, and finally the output or performance for...
Also referred to as artificial neural networks (ANNs), neural nets or deep neural networks, neural networks represent a type of deep learning technology that's classified under the broader field of artificial intelligence (AI). Neural networks are widely used in a variety of applications, including...