Computers in biology and medicine
Oct 5, 2022
BACKGROUND: Current spine models for analog bench models, surgical navigation and training platforms are conventionally based on 3D models from anatomical human body polygon database or from time-consuming manual-labelled data. This work proposed a w...
Computer methods and programs in biomedicine
Oct 5, 2022
BACKGROUND AND OBJECTIVE: Treatment effect estimation, as a fundamental problem in causal inference, focuses on estimating the outcome difference between different treatments. However, in clinical observational data, some patient covariates (such as ...
Sensors (Basel, Switzerland)
Oct 5, 2022
In recent years, network traffic contains a lot of feature information. If there are too many redundant features, the computational cost of the algorithm will be greatly increased. This paper proposes an anomalous network traffic detection method bas...
Scientific reports
Oct 5, 2022
Monocular depth estimation aims to recover the depth information in three-dimensional (3D) space from a single image efficiently, but it is an ill-posed problem. Recently, Transformer-based architectures have achieved excellent accuracy in monocular ...
Scientific reports
Oct 5, 2022
Dual switching system is a special hybrid system that contains both deterministic and stochastic switching subsystems. Due to its complex switching mechanism, few studies have been conducted for dual switching systems, especially for systems with unc...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
We are motivated by the real challenges presented in a human-robot system to develop new designs that are efficient at data level and with performance guarantees, such as stability and optimality at system level. Existing approximate/adaptive dynamic...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
The unified criteria are analyzed on the global dissipativity and stability for the delayed fractional-order systems of multidimension-valued memristive neural networks (FSMVMNNs) in this article. First, based on the comprehensive knowledge about mul...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
One of the pillar generative machine learning approaches in time series data study and analysis is the hidden Markov model (HMM). Early research focused on the speech recognition application of the model with later expansion into numerous fields, inc...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
The timing of individual neuronal spikes is essential for biological brains to make fast responses to sensory stimuli. However, conventional artificial neural networks lack the intrinsic temporal coding ability present in biological networks. We prop...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
Class imbalance is a prevalent phenomenon in various real-world applications and it presents significant challenges to model learning, including deep learning. In this work, we embed ensemble learning into the deep convolutional neural networks (CNNs...