Neural networks : the official journal of the International Neural Network Society
Nov 4, 2014
The problem of global exponential stability in mean square of delayed Markovian jump fuzzy cellular neural networks (DMJFCNNs) with generally uncertain transition rates (GUTRs) is investigated in this paper. In this GUTR neural network model, each tr...
IEEE transactions on neural networks and learning systems
Jul 14, 2014
Monocular multiple-object tracking is a fundamental yet under-addressed computer vision problem. In this paper, we propose a novel learning framework for tracking multiple objects by detection. First, instead of heuristically defining a tracking algo...
Reinforcement learning (RL) enables an agent to learn behavior by acquiring experience through trial-and-error interactions with a dynamic environment. However, knowledge is usually built from scratch and learning to behave may take a long time. Here...
OBJECTIVE: The LungFlag risk prediction model uses individualized clinical variables to identify individuals at high-risk of non-small cell lung cancer (NSCLC) for screening with low-dose computed tomography (LDCT). This study evaluates the cost-effe...
Degeneracy-the ability of different structures to perform the same function-is a fundamental feature of biological systems, contributing to their robustness and evolvability. However, the ubiquity of degeneracy in systems generated through adaptive p...
Aging clinical and experimental research
May 13, 2025
BACKGROUND: Osteoporosis is often underdiagnosed due to limitations in traditional screening methods, leading to missed early intervention opportunities. AI-driven screening using chest radiographs could improve early detection, reduce fracture risk,...
Journal of neuroengineering and rehabilitation
May 12, 2025
BACKGROUND: Gait quality indices, such as the Gillette Gait Index or Gait Profile Score (GPS), can provide clinicians with objective, straightforward measures to quantify gait pathology and monitor changes over time. However, these methods often requ...
Heterogeneous treatment effect estimation is an important problem in precision medicine. Specific interests lie in identifying the differential effect of different treatments based on some external covariates. We propose a novel non-parametric treatm...
This paper proposes a neural network based on the Markov probability transition matrix to predict the training performance of football athletes. Firstly, seven training indicators affecting the training performance are designed by the Event-group tra...
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