AIMC Topic: Neural Networks, Computer

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Towards Adversarial Robustness for Multi-Mode Data through Metric Learning.

Sensors (Basel, Switzerland)
Adversarial attacks have become one of the most serious security issues in widely used deep neural networks. Even though real-world datasets usually have large intra-variations or multiple modes, most adversarial defense methods, such as adversarial ...

Analysis of Friction Noise Mechanism in Lead Screw System of Autonomous Vehicle Seats and Dynamic Instability Prediction Based on Deep Neural Network.

Sensors (Basel, Switzerland)
This study investigated the squeal mechanism induced by friction in a lead screw system. The dynamic instability in the friction noise model of the lead screw was derived through a complex eigenvalue analysis via a finite element model. A two degree ...

CS-based multi-task learning network for arrhythmia reconstruction and classification using ECG signals.

Physiological measurement
. Although deep learning-based current methods have achieved impressive results in electrocardiograph (ECG) arrhythmia classification issues, they rely on using the original data to identify arrhythmia categories. However, a large amount of data gene...

Au-Ag OHCs-based SERS sensor coupled with deep learning CNN algorithm to quantify thiram and pymetrozine in tea.

Food chemistry
Pesticide residue detection in food has become increasingly important. Herein, surface-enhanced Raman scattering (SERS) coupled with an intelligent algorithm was developed for the rapid and sensitive detection of pesticide residues in tea. By employi...

Bridge Damage Identification Using Deep Neural Networks on Time-Frequency Signals Representation.

Sensors (Basel, Switzerland)
For the purpose of maintaining and prolonging the service life of civil constructions, structural damage must be closely monitored. Monitoring the incidence, formation, and spread of damage is crucial to ensure a structure's ongoing performance. This...

Cross-Domain Indoor Visual Place Recognition for Mobile Robot via Generalization Using Style Augmentation.

Sensors (Basel, Switzerland)
The article presents an algorithm for the multi-domain visual recognition of an indoor place. It is based on a convolutional neural network and style randomization. The authors proposed a scene classification mechanism and improved the performance of...

Analytical interpretation of the gap of CNN's cognition between SAR and optical target recognition.

Neural networks : the official journal of the International Neural Network Society
Synthetic aperture radar (SAR) automatic target recognition (ATR) is a crucial technique utilized in various scenarios of geoscience and remote sensing. Despite the remarkable success of convolutional neural networks (CNNs) in optical vision tasks, t...

Neurodynamic optimization approaches with finite/fixed-time convergence for absolute value equations.

Neural networks : the official journal of the International Neural Network Society
This paper proposes three novel accelerated inverse-free neurodynamic approaches to solve absolute value equations (AVEs). The first two are finite-time converging approaches and the third one is a fixed-time converging approach. It is shown that the...

Safe control of logical control networks with random impulses.

Neural networks : the official journal of the International Neural Network Society
Under the framework of a hybrid-index model, this paper investigates safe control problems of state-dependent random impulsive logical control networks (RILCNs) on both finite and infinite horizons, respectively. By using the ΞΎ-domain method and the ...

Machine learning-based model predictive controller design for cell culture processes.

Biotechnology and bioengineering
The biopharmaceutical industry continuously seeks to optimize the critical quality attributes to maintain the reliability and cost-effectiveness of its products. Such optimization demands a scalable and optimal control strategy to meet the process co...