BACKGROUND: Accurate classification of focal cortical dysplasia (FCD) has been challenging due to the problematic visual detection in magnetic resonance imaging (MRI). Hence, recently, there has been a necessity for employing new techniques to solve ...
Neural networks : the official journal of the International Neural Network Society
Aug 18, 2022
In this paper, a synergetic learning structure-based neuro-optimal fault tolerant control (SLSNOFTC) method is proposed for unknown nonlinear continuous-time systems with actuator failures. Under the framework of the synergetic learning structure (SL...
Journal of computational biology : a journal of computational molecular cell biology
Aug 18, 2022
The detection and classification of nuclei play an important role in the histopathological analysis. It aims to find out the distribution of nuclei in the histopathology images for the next step of analysis and research. However, it is very challengi...
The journal of physical chemistry letters
Aug 18, 2022
Machine-learning force fields have become increasingly popular because of their balance of accuracy and speed. However, a significant limitation is the use of element-specific features, leading to poor scalability with the number of elements. This wo...
A large number of experiments have proved that the ring structure is a common phenomenon in neural networks. Nevertheless, a few works have been devoted to studying the neurodynamics of networks with only one ring. Little is known about the dynamics ...
Multisensor fusion-based road segmentation plays an important role in the intelligent driving system since it provides a drivable area. The existing mainstream fusion method is mainly to feature fusion in the image space domain which causes the persp...
In this article, subject to time-varying delay and uncertainties in dynamics, we propose a novel adaptive fixed-time control strategy for a class of nonlinear bilateral teleoperation systems. First, an adaptive control scheme is applied to estimate t...
Existing network embedding algorithms based on generative adversarial networks (GANs) improve the robustness of node embeddings by selecting high-quality negative samples with the generator to play against the discriminator. Since most of the negativ...
In recent years, the appearance of the broad learning system (BLS) is poised to revolutionize conventional artificial intelligence methods. It represents a step toward building more efficient and effective machine-learning methods that can be extende...
This article investigates the reinforcement-learning (RL)-based disturbance rejection control for uncertain nonlinear systems having nonsimple nominal models. An extended state observer (ESO) is first designed to estimate the system state and the tot...
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