AIMC Topic: Algorithms

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Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints.

Neural networks : the official journal of the International Neural Network Society
We introduce Constr-DRKM, a deep kernel method for the unsupervised learning of disentangled data representations. We propose augmenting the original deep restricted kernel machine formulation for kernel PCA by orthogonality constraints on the latent...

DDosTC: A Transformer-Based Network Attack Detection Hybrid Mechanism in SDN.

Sensors (Basel, Switzerland)
Software-defined networking (SDN) has emerged in recent years as a form of Internet architecture. Its scalability, dynamics, and programmability simplify the traditional Internet structure. This architecture realizes centralized management by separat...

Evaluation of Effect of Curcumin on Psychological State of Patients with Pulmonary Hypertension by Magnetic Resonance Image under Deep Learning.

Contrast media & molecular imaging
This research aimed to evaluate the right ventricular segmentation ability of magnetic resonance imaging (MRI) images based on deep learning and evaluate the influence of curcumin (Cur) on the psychological state of patients with pulmonary hypertensi...

Diagnosis and Treatment Effect of Convolutional Neural Network-Based Magnetic Resonance Image Features on Severe Stroke and Mental State.

Contrast media & molecular imaging
The purpose of this paper is to explore the impact of magnetic resonance imaging (MRI) image features based on convolutional neural network (CNN) algorithm and conditional random field on the diagnosis and mental state of patients with severe stroke....

Artificial intelligence-driven phenotyping of zebrafish psychoactive drug responses.

Progress in neuro-psychopharmacology & biological psychiatry
Zebrafish (Danio rerio) are rapidly emerging in biomedicine as promising tools for disease modelling and drug discovery. The use of zebrafish for neuroscience research is also growing rapidly, necessitating novel reliable and unbiased methods of neur...

Intelligent Network Applications Monitoring and Diagnosis Employing Software Sensing and Machine Learning Solutions.

Sensors (Basel, Switzerland)
The article presents a research in the field of complex sensing, detection, and recovery of communications networks applications and hardware, in case of failures, maloperations, or unauthorized intrusions. A case study, based on Davis AI engine oper...

Deep grey matter quantitative susceptibility mapping from small spatial coverages using deep learning.

Zeitschrift fur medizinische Physik
INTRODUCTION: Quantitative Susceptibility Mapping (QSM) is generally acquired with full brain coverage, even though many QSM brain-iron studies focus on the deep grey matter (DGM) region only. Reducing the spatial coverage to the DGM vicinity can sub...

Bio-instantiated recurrent neural networks: Integrating neurobiology-based network topology in artificial networks.

Neural networks : the official journal of the International Neural Network Society
Biological neuronal networks (BNNs) are a source of inspiration and analogy making for researchers that focus on artificial neuronal networks (ANNs). Moreover, neuroscientists increasingly use ANNs as a model for the brain. Despite certain similariti...

Artificial Intelligence-Enabled Electrocardiography to Screen Patients with Dilated Cardiomyopathy.

The American journal of cardiology
Undiagnosed dilated cardiomyopathy (DC) can be asymptomatic or present as sudden cardiac death, therefore pre-emptively identifying and treating patients may be beneficial. Screening for DC with echocardiography is expensive and labor intensive and s...