AIMC Topic: Artificial Intelligence

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Efficient Computation Reduction in Bayesian Neural Networks Through Feature Decomposition and Memorization.

IEEE transactions on neural networks and learning systems
The Bayesian method is capable of capturing real-world uncertainties/incompleteness and properly addressing the overfitting issue faced by deep neural networks. In recent years, Bayesian neural networks (BNNs) have drawn tremendous attention to artif...

A Survey on Learning-Based Approaches for Modeling and Classification of Human-Machine Dialog Systems.

IEEE transactions on neural networks and learning systems
With the rapid development from traditional machine learning (ML) to deep learning (DL) and reinforcement learning (RL), dialog system equipped with learning mechanism has become the most effective solution to address human-machine interaction proble...

Finite-Time Tracking Control for Nonlinear Systems via Adaptive Neural Output Feedback and Command Filtered Backstepping.

IEEE transactions on neural networks and learning systems
This article is concerned with the tracking control problem for uncertain high-order nonlinear systems in the presence of input saturation. A finite-time control strategy combined with neural state observer and command filtered backstepping is propos...

Iterative Dynamic Generic Learning for Face Recognition From a Contaminated Single-Sample Per Person.

IEEE transactions on neural networks and learning systems
This article focuses on a new and practical problem in single-sample per person face recognition (SSPP FR), i.e., SSPP FR with a contaminated biometric enrolment database (SSPP-ce FR), where the SSPP-based enrolment database is contaminated by nuisan...

Artificial Intelligence in Hypertension: Seeing Through a Glass Darkly.

Circulation research
Hypertension remains the largest modifiable cause of mortality worldwide despite the availability of effective medications and sustained research efforts over the past 100 years. Hypertension requires transformative solutions that can help reduce the...

Artificial Intelligence Efficiently Identifies Regional Differences in the Progression of Tomographic Parameters of Keratoconic Corneas.

Journal of refractive surgery (Thorofare, N.J. : 1995)
PURPOSE: To develop an artificial intelligence (AI) model to effectively assess local versus global progression of keratoconus using multiple tomographic parameters.

Relationship between Artificial Intelligence-Based General Anesthetics and Postoperative Cognitive Dysfunction.

Journal of healthcare engineering
Postoperative cognitive dysfunction (POCD) refers to the complications of the central nervous system before and after surgery in patients without mental disorders. Many studies have shown that surgical anesthesia may cause POCD, especially in elderly...

JRL-YOLO: A Novel Jump-Join Repetitious Learning Structure for Real-Time Dangerous Object Detection.

Computational intelligence and neuroscience
Campus security incidents occur from time to time, which seriously affect the public security. In recent years, the rapid development of artificial intelligence has brought technical support for campus intelligent security. In order to quickly recogn...