AI Medical Compendium Topic:
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Analysis of Human Information Recognition Model in Sports Based on Radial Basis Fuzzy Neural Network.

Computational intelligence and neuroscience
In sports, because the movement of the human body is composed of the movements of the human limbs, and the complex and changeable movements of the human limbs lead to various and complicated movement modes of the entire human body, it is not easy to ...

A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data.

Scientific reports
Training on multiple diverse data sources is critical to ensure unbiased and generalizable AI. In healthcare, data privacy laws prohibit data from being moved outside the country of origin, preventing global medical datasets being centralized for AI ...

Rolling Bearing Fault Diagnosis Based on Markov Transition Field and Residual Network.

Sensors (Basel, Switzerland)
Data-driven rolling-bearing fault diagnosis methods are mostly based on deep-learning models, and their multilayer nonlinear mapping capability can improve the accuracy of intelligent fault diagnosis. However, problems such as gradient disappearance ...

CAEVT: Convolutional Autoencoder Meets Lightweight Vision Transformer for Hyperspectral Image Classification.

Sensors (Basel, Switzerland)
Convolutional neural networks (CNNs) have been prominent in most hyperspectral image (HSI) processing applications due to their advantages in extracting local information. Despite their success, the locality of the convolutional layers within CNNs re...

RL-DOVS: Reinforcement Learning for Autonomous Robot Navigation in Dynamic Environments.

Sensors (Basel, Switzerland)
Autonomous navigation in dynamic environments where people move unpredictably is an essential task for service robots in real-world populated scenarios. Recent works in reinforcement learning (RL) have been applied to autonomous vehicle driving and t...

Inference-Based Posteriori Parameter Distribution Optimization.

IEEE transactions on cybernetics
Encouraging the agent to explore has always been an important and challenging topic in the field of reinforcement learning (RL). Distributional representation for network parameters or value functions is usually an effective way to improve the explor...

A Deep-Ensemble-Level-Based Interpretable Takagi-Sugeno-Kang Fuzzy Classifier for Imbalanced Data.

IEEE transactions on cybernetics
Existing research reveals that the misclassification rate for imbalanced data depends heavily on the problematic areas due to the existence of small disjoints, class overlap, borderline, and rare data samples. In this study, by stacking zero-order Ta...

Semisupervised Multiple Choice Learning for Ensemble Classification.

IEEE transactions on cybernetics
Ensemble learning has many successful applications because of its effectiveness in boosting the predictive performance of classification models. In this article, we propose a semisupervised multiple choice learning (SemiMCL) approach to jointly train...

Hybrid Model-Based Emotion Contextual Recognition for Cognitive Assistance Services.

IEEE transactions on cybernetics
Endowing ubiquitous robots with cognitive capabilities for recognizing emotions, sentiments, affects, and moods of humans in their context is an important challenge, which requires sophisticated and novel approaches of emotion recognition. Most studi...

Novel Multitask Conditional Neural-Network Surrogate Models for Expensive Optimization.

IEEE transactions on cybernetics
Multiple-related tasks can be learned simultaneously by sharing information among tasks to avoid tabula rasa learning and to improve performance in the no transfer case (i.e., when each task learns in isolation). This study investigates multitask lea...