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Sliding mode synchronization of uncertain memristor cellular neural network and application in secure communication
The purpose of this research is to investigate the synchronization and control for uncertain memristor-based cellular neural network and its...
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CA-NN: a cellular automata neural network for handwritten pattern recognition
Convolutional neural networks (CNNs) are best suited for image data. The most important layer in CNNs is the convolution layer. In this paper,...
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Shunting Inhibitory Cellular Neural Networks
The chapter delves into the dynamics of shunting inhibitory cellular neural networks encompassing continuous and discontinuous behaviors. The initial...
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Heterogeneous wireless network selection using feed forward double hierarchy linguistic neural network
Network selection in heterogeneous wireless networks (HWNs) is a complex issue that requires a thorough understanding of service features and user...
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Circuit simulation and image encryption based on a six-dimensional cellular neural network hyperchaotic system
This paper proposes a six-dimensional hyperchaotic system based on the Cellular Neural Networks (CNN) theory. Numerical analysis of the Lyapunov...
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Graph neural network approaches for single-cell data: a recent overview
Graph neural networks (GNNs) are reshaping our understanding of biomedicine and diseases by revealing the deep connections among genes and cells. As...
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Interpreting single-cell and spatial omics data using deep neural network training dynamics
Single-cell and spatial omics datasets can be organized and interpreted by annotating single cells to distinct types, states, locations or...
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Convolutional neural network for classifying the stages of the cell cycle
The cell cycle is a highly coordinated process that ensures the duplication and transmission of genetic information from one cell generation to the...
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HEN: a novel hybrid explainable neural network based framework for robust network intrusion detection
With the rapid development of network technology and the automation process for 5G, cyber-attacks have become increasingly complex and threatening....
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Efficient Simulation of Non-uniform Cellular Automata with a Convolutional Neural Network
Cellular automata (CAs) and convolutional neural networks (CNNs) are closely related due to the local nature of information processing. The...
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Radial Basis Gated Unit-Recurrent Neural Network (RBGU-RNN) Algorithm
Radial Basis Gated Unit-Recurrent Neural Network (RBGU-RNN) algorithm is a new architecture-based on recurrent neural network which combines a Radial...
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Neural Cellular Automaton for Decentralized Inference in Distributed Manipulation Systems
Distributed manipulation systems employ a grid of independently controlled actuators to achieve precise manipulation of objects resting on their...
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Quasi-projective Synchronization Control of Delayed Stochastic Quaternion-Valued Fuzzy Cellular Neural Networks with Mismatched Parameters
This paper deals with the quasi-projective synchronization problem of delayed stochastic quaternion fuzzy cellular neural networks with mismatch...
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Topological numbers in uniform intuitionistic fuzzy environment and their application in neural network
Intuitionistic Fuzzy sets combine the ideas of uniformity, membership, and non-membership grades of the elements. Similarly, Intuitionistic Fuzzy...
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Crowd Movement Type Estimation in Video by Integral Optical Flow and Convolution Neural Network
AbstractThe paper proposes a new approach for crowd movement type estimation in video by combining convolutional neural network and integral optical...
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Enhancing plant nutritional deficiency analysis: a multi-attention convolutional neural network approach
Accurately identifying plant nutritional deficiencies is crucial for promoting optimal growth and productivity. Nutritional deficiency changes plant...
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A novel dual-layer security scheme based on 3-cell cellular neural network encryption and data hiding scheme for color images
The security of digital information is one of the significant problems of the existing world. In this work, we have proposed a dual-layer information...
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A probabilistic spatio-temporal neural network to forecast COVID-19 counts
Geo-referenced and temporal data are becoming more and more ubiquitous in a wide range of fields such as medicine and economics. Particularly in the...
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Learning microstructure–property mapping via label-free 3D convolutional neural network
Predicting the physical property of a class of microstructures is crucial in material design, structural simulation, and design. Property prediction...
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Hierarchical convolution neural network models for classifying the segmented OCT and OCTA images using U-Net model
The accurate prediction and identification of Alzheimer’s disease and Choroidal Neovascularization using Optical Coherence Tomography and Optical...
