Search
Search Results
-
Combining graph neural network with deep reinforcement learning for resource allocation in computing force networks
Fueled by the explosive growth of ultra-low-latency and real-time applications with specific computing and network performance requirements, the...
-
Reconfigurable spatial-parallel stochastic computing for accelerating sparse convolutional neural networks
Edge devices play an increasingly important role in the convolutional neural network (CNN) inference. However, the large computation and storage...
-
Edge computing-oriented smart agricultural supply chain mechanism with auction and fuzzy neural networks
Powered by data-driven technologies, precision agriculture offers immense productivity and sustainability benefits. However, fragmentation across...
-
Leveraging Quantum computing for synthetic image generation and recognition with Generative Adversarial Networks and Convolutional Neural Networks
The generation and classification of synthetic images is a challenging and important task in the digital age. Generative Adversarial Networks are...
-
Edge-cloud computing oriented large-scale online music education mechanism driven by neural networks
With the advent of the big data era, edge cloud computing has developed rapidly. In this era of popular digital music, various technologies have...
-
Exploring the distributed learning on federated learning and cluster computing via convolutional neural networks
Distributed learning has led to the development of federated learning and cluster computing; however, the two methods are very different. Therefore,...
-
On Fast Computing of Neural Networks Using Central Processing Units
AbstractThis work is devoted to methods for creating fast and accurate neural network algorithms for central processors, which were proposed by...
-
Accelerating neural network architecture search using multi-GPU high-performance computing
Neural networks stand out from artificial intelligence because they can complete challenging tasks, such as image classification. However, designing...
-
Dependent Task Scheduling Using Parallel Deep Neural Networks in Mobile Edge Computing
Conventional detection techniques aimed at intelligent devices rely primarily on deep learning algorithms, which, despite their high precision, are...
-
Robot knowledge analysis based on cognitive computing and modular neural network feature combination
With the ongoing integration of information technology and industrialization, strategic emerging industries are becoming an increasingly important...
-
Hardware Spiking Neural Networks with Pair-Based STDP Using Stochastic Computing
Spiking Neural Networks (SNNs) can closely mimic the biological neural network systems. Recently, the SNNs have been developed in hardware circuits...
-
Nonlinear Dynamics and Computing in Recurrent Neural Networks
Nonlinearity is a key concept in the design and implementation of photonic neural networks for computing. This chapter introduces the fundamental...
-
A convolutional neural network based online teaching method using edge-cloud computing platform
Teaching has become a complex essential tool for students’ abilities, due to their different levels of learning and understanding. In the traditional...
-
Optimal urban competitiveness assessment using cloud computing and neural network
In the network economy domain, urban competitiveness refers to the comparison between cities in terms of competition and development. It is the...
-
Hyperparameter optimization method based on dynamic Bayesian with sliding balance mechanism in neural network for cloud computing
Hyperparameter optimization (HPO) of deep neural networks plays an important role of performance and efficiency of detection networks. Especially for...
-
An Edge Computing System for Fast Image Recognition Based on Convolutional Neural Network and Petri Net Model
As a computer system can precisely detect some target objects, many application scenarios will be developed. In this study, the customized object...
-
An autonomous architecture based on reinforcement deep neural network for resource allocation in cloud computing
Today, cloud computing technology has attracted the attention of many researchers. According to the needs of users to quickly execute requests and...
-
Heterogeneous gradient computing optimization for scalable deep neural networks
Nowadays, data processing applications based on neural networks cope with the growth in the amount of data to be processed and with the increase in...
-
Intelligent quantitative safety monitoring approach for ATP system by neural computing and probabilistic model checking
Online quantitative safety monitoring is the key technology for ensuring the operational safety of the automatic train protection (ATP) system for...
-
Semi-global fixed/predefined-time RNN models with comprehensive comparisons for time-variant neural computing
This paper concerns with the time-variant neural computing in a semi-global sense, taking into account initial conditions located within a region...
