AIMC Topic: Uncertainty

Clear Filters Showing 351 to 360 of 737 articles

Development of a Relative Similarity Degree Based Engineering Construction Multi-Attribute Decision Model and Its Application.

Computational intelligence and neuroscience
Generally, there are large amounts of uncertain factors in the multi-attribute decision system. By using the gray relational degree and fuzzy gray relational degree, the weights of the comprehensive indexes are extracted. Then, a novel decision model...

Remaining Useful Life Prediction Method for Bearings Based on LSTM with Uncertainty Quantification.

Sensors (Basel, Switzerland)
To reduce the economic losses caused by bearing failures and prevent safety accidents, it is necessary to develop an effective method to predict the remaining useful life (RUL) of the rolling bearing. However, the degradation inside the bearing is di...

Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency.

Medical image analysis
Despite that Convolutional Neural Networks (CNNs) have achieved promising performance in many medical image segmentation tasks, they rely on a large set of labeled images for training, which is expensive and time-consuming to acquire. Semi-supervised...

Uncertainty-Aware Deep Learning With Cross-Task Supervision for PHE Segmentation on CT Images.

IEEE journal of biomedical and health informatics
Perihematomal edema (PHE) volume, surrounding spontaneous intracerebral hemorrhage (SICH), is an important biomarker for the presence of SICH-associated diseases. However, due to irregular shapes and extremely low contrast of PHE on CT images, manual...

Finite-Time H State Estimation for PDT-Switched Genetic Regulatory Networks With Randomly Occurring Uncertainties.

IEEE/ACM transactions on computational biology and bioinformatics
This article is concerned with the problem of finite-time H state estimation for switched genetic regulatory networks with randomly occurring uncertainties. The persistent dwell-time switching rule, as a more versatile class of switching rules, is co...

NPBDREG: Uncertainty assessment in diffeomorphic brain MRI registration using a non-parametric Bayesian deep-learning based approach.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Quantification of uncertainty in deep-neural-networks (DNN) based image registration algorithms plays a critical role in the deployment of image registration algorithms for clinical applications such as surgical planning, intraoperative guidance, and...

Improving Medical Images Classification With Label Noise Using Dual-Uncertainty Estimation.

IEEE transactions on medical imaging
Deep neural networks are known to be data-driven and label noise can have a marked impact on model performance. Recent studies have shown great robustness to classic image recognition even under a high noisy rate. In medical applications, learning fr...

An Optimization Model for Appraising Intrusion-Detection Systems for Network Security Communications: Applications, Challenges, and Solutions.

Sensors (Basel, Switzerland)
Cyber-attacks are getting increasingly complex, and as a result, the functional concerns of intrusion-detection systems (IDSs) are becoming increasingly difficult to resolve. The credibility of security services, such as privacy preservation, authent...

Robust adaptive fault detection and diagnosis observer design for a class of nonlinear systems with uncertainty and unknown time-varying internal delay.

ISA transactions
This paper introduces a novel robust adaptive fault detection and diagnosis (FDD) observer design approach for a class of nonlinear systems with parametric uncertainty, unknown system fault and time-varying internal delays. The conditions for the exi...

Adaptive 2-bits-triggered neural control for uncertain nonlinear multi-agent systems with full state constraints.

Neural networks : the official journal of the International Neural Network Society
This paper investigates an adaptive 2-bits-triggered neural control for a class of uncertain nonlinear multi-agent systems (MASs) with full state constraints. Considering the limitations of practical physical devices and operating conditions, MASs ma...