AIMC Topic: Algorithms

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Finite-time H output synchronization for DCRDNNs with multiple delayed and adaptive output couplings.

Neural networks : the official journal of the International Neural Network Society
This work concentrates on solving the finite-time H output synchronization (FTHOS) issue of directed coupled reaction-diffusion neural networks (DCRDNNs) with multiple delayed and adaptive output couplings in the presence of external disturbances. Ba...

VCSAP: Online reinforcement learning exploration method based on visitation count of state-action pairs.

Neural networks : the official journal of the International Neural Network Society
In the domain of online reinforcement learning, strategies that leverage inherent rewards for exploration tend to achieve commendable outcomes within contexts characterized by deceptive or sparse rewards. Counting through the visitation of states is ...

Spectral adversarial attack on graph via node injection.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have shown remarkable achievements and have been extensively applied in various downstream tasks, such as node classification and community detection. However, recent studies have demonstrated that GNNs are vulnerable to ...

CS-QCFS: Bridging the performance gap in ultra-low latency spiking neural networks.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNNs) are at the forefront of computational neuroscience, emulating the nuanced dynamics of biological systems. In the realm of SNN training methods, the conversion from ANNs to SNNs has generated significant interest due to ...

An ensemble learning method combined with multiple feature representation strategies to predict lncRNA subcellular localizations.

Computational biology and chemistry
Long non-coding RNAs (lncRNAs) are strongly associated with cellular physiological mechanisms and implicated in the numerous diseases. By exploring the subcellular localizations of lncRNAs, we can not only gain crucial insights into the molecular mec...

Hybrid deep learning for computational precision in cardiac MRI segmentation: Integrating Autoencoders, CNNs, and RNNs for enhanced structural analysis.

Computers in biology and medicine
Recent advancements in cardiac imaging have been significantly enhanced by integrating deep learning models, offering transformative potential in early diagnosis and patient care. The research paper explores the application of hybrid deep learning me...

Vision Sensor for Automatic Recognition of Human Activities via Hybrid Features and Multi-Class Support Vector Machine.

Sensors (Basel, Switzerland)
Over recent years, automated Human Activity Recognition (HAR) has been an area of concern for many researchers due to its widespread application in surveillance systems, healthcare environments, and many more. This has led researchers to develop cohe...

Implementing an AI algorithm in the clinical setting: a case study for the accuracy paradox.

European radiology
OBJECTIVES: We report our experience implementing an algorithm for the detection of large vessel occlusion (LVO) for suspected stroke in the emergency setting, including its performance, and offer an explanation as to why it was poorly received by ra...

Enhancing Recommender Systems through Imputation and Social-Aware Graph Convolutional Neural Network.

Neural networks : the official journal of the International Neural Network Society
Recommendation systems are vital tools for helping users discover content that suits their interests. Collaborative filtering methods are one of the techniques employed for analyzing interactions between users and items, which are typically stored in...