AIMC Topic: Uncertainty

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Multistability and Stabilization of Fractional-Order Competitive Neural Networks With Unbounded Time-Varying Delays.

IEEE transactions on neural networks and learning systems
This article investigates the multistability and stabilization of fractional-order competitive neural networks (FOCNNs) with unbounded time-varying delays. By utilizing the monotone operator, several sufficient conditions of the coexistence of equili...

EpICC: A Bayesian neural network model with uncertainty correction for a more accurate classification of cancer.

Scientific reports
Accurate classification of cancers into their types and subtypes holds the key for choosing the right treatment strategy and can greatly impact patient well-being. However, existence of large-scale variations in the molecular processes driving even a...

Uncertainty teacher with dense focal loss for semi-supervised medical image segmentation.

Computers in biology and medicine
In medical scenarios, obtaining pixel-level annotations for medical images is expensive and time-consuming, even if considering its importance for automating segmentation tasks. Due to the scarcity of labels in the training phase, semi-supervised met...

Uncertainty-aware deep co-training for semi-supervised medical image segmentation.

Computers in biology and medicine
Semi-supervised learning has made significant strides in the medical domain since it alleviates the heavy burden of collecting abundant pixel-wise annotated data for semantic segmentation tasks. Existing semi-supervised approaches enhance the ability...

Reinforcement-Learning-Based Disturbance Rejection Control for Uncertain Nonlinear Systems.

IEEE transactions on cybernetics
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...

Time-Synchronized Control for Disturbed Systems.

IEEE transactions on cybernetics
Finite-time control is concerned with steering a system state to the origin before a certain settling-time limit, ignoring any consideration of when each state element converges relative to the others. In this article, a control problem called time-s...

A Bayesian deep learning method for freeway incident detection with uncertainty quantification.

Accident; analysis and prevention
Incident detection is fundamental for freeway management to reduce non-recurrent congestions and secondary incidents. Recently, machine learning technologies have made considerable progress in the incident detection field, but many still face challen...

Distance and similarity measures for normal wiggly dual hesitant fuzzy sets and their application in medical diagnosis.

Scientific reports
The normal wiggly dual hesitant fuzzy set (NWDHFS) is a modern mathematical tool that can be used to express the deep ideas of membership and non-membership information hidden in the thought-level of decision-makers (DMs). To enhance and expand the a...

iCVM: An Interpretable Deep Learning Model for CVM Assessment Under Label Uncertainty.

IEEE journal of biomedical and health informatics
The Cervical Vertebral Maturation (CVM) method aims to determine the craniofacial skeletal maturational stage, which is crucial for orthodontic and orthopedic treatment. In this paper, we explore the potential of deep learning for automatic CVM asses...

Estimation and uncertainty analysis of groundwater quality parameters in a coastal aquifer under seawater intrusion: a comparative study of deep learning and classic machine learning methods.

Environmental science and pollution research international
Excessive withdrawal of groundwater for agricultural irrigation can cause seawater intrusion into coastal aquifers. Such a case will in turn results in deterioration of irrigation water quality. Determination of irrigation water quality with traditio...