This article considers the synchronization problem of delayed reaction-diffusion neural networks via quantized sampled-data (SD) control under spatially point measurements (SPMs), where distributed and discrete delays are considered. The synchronizat...
Reflection caused by glass often degrades the quality of an image and further makes it difficult to estimate depth. In this article, we propose joint reflection removal and depth estimation from a single image. We perform reflection removal (transmis...
Retrieving informative images from the large-scale aurora data is of great significance in the field of space physics. In this article, we propose a hierarchical deep embedding (HDE) model to assist scientists for their aurora image retrieval. Other ...
Computational intelligence and neuroscience
Dec 22, 2021
With the development of neural networks in deep learning, artificial intelligence machine learning has become the main focus of researchers. In College English grammar detection, oral grammar is the most error rate content. So, this paper optimizes M...
Clinical metagenomics is a powerful diagnostic tool, as it offers an open view into all DNA in a patient's sample. This allows the detection of pathogens that would slip through the cracks of classical specific assays. However, due to this unspecific...
AIMS: The purpose of this study was to construct a model for oral assessment using deep learning image recognition technology and to verify its accuracy.
PURPOSE: To introduce a novel convolutional neural network (CNN)-based approach for frequency-and-phase correction (FPC) of MR spectroscopy (MRS) spectra to achieve fast and accurate FPC of single-voxel MEGA-PRESS MRS data.
Neural networks : the official journal of the International Neural Network Society
Dec 21, 2021
This paper investigates the problem of adaptive tracking control for a class of nonlinear multi-input and multi-output (MIMO) state-constrained systems with input delay and saturation. During the process of the control scheme, neural network is emplo...
Neural networks : the official journal of the International Neural Network Society
Dec 21, 2021
Measure-preserving neural networks are well-developed invertible models, however, their approximation capabilities remain unexplored. This paper rigorously analyzes the approximation capabilities of existing measure-preserving neural networks includi...
Memory is a dynamic process that is based on and can be altered by experiences. Integrating memories of multiple experiences (memory integration) is the basis of flexible and complex decision-making. However, the mechanism of memory integration in ne...
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