System logs are a crucial component of system maintainability, as they record the status of the system and essential events for troubleshooting and maintenance when necessary. Therefore, anomaly detection of system logs is crucial. Recent research ha...
. Deep Learning models are often susceptible to failures after deployment. Knowing when your model is producing inadequate predictions is crucial. In this work, we investigate the utility of Monte Carlo (MC) dropout and the efficacy of the proposed u...
What drives children to explore and learn when external rewards are uncertain or absent? Across three studies, we tested whether information gain itself acts as an internal reward and suffices to motivate children's actions. We measured 24-56-month-o...
IEEE transactions on bio-medical engineering
May 19, 2023
OBJECTIVE: Convolutional neural networks (CNNs) have demonstrated promise in automated cardiac magnetic resonance image segmentation. However, when using CNNs in a large real-world dataset, it is important to quantify segmentation uncertainty and ide...
Artificial Intelligence (AI) tools are being developed to assist with increasingly complex diagnostic tasks in medicine. This produces epistemic disruption in diagnostic processes, even in the absence of AI itself, through the datafication and digita...
Uncertainty estimation is crucial for understanding the reliability of deep learning (DL) predictions, and critical for deploying DL in the clinic. Differences between training and production datasets can lead to incorrect predictions with underestim...
Semi-supervised learning (SSL) methods show their powerful performance to deal with the issue of data shortage in the field of medical image segmentation. However, existing SSL methods still suffer from the problem of unreliable predictions on unanno...
Popular semi-supervised medical image segmentation networks often suffer from error supervision from unlabeled data since they usually use consistency learning under different data perturbations to regularize model training. These networks ignore the...
Traditional Chinese medicine (TCM) has gradually played an indispensable role in people's health maintenance, especially in the treatment of chronic diseases. However, there is always uncertainty and hesitation in the judgment and understanding of di...
Neural networks : the official journal of the International Neural Network Society
Apr 28, 2023
The stabilization problem is studied for memristive neural networks with interval delays under aperiodic switching event-triggered control. Note that, most of delayed memristive neural networks models studied are discontinuous, which are not the real...