AI Medical Compendium Topic

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Automatic Classification of Rotor Faults in Soft-Started Induction Motors, Based on Persistence Spectrum and Convolutional Neural Network Applied to Stray-Flux Signals.

Sensors (Basel, Switzerland)
Due to their robustness, versatility and performance, induction motors (IMs) have been widely used in many industrial applications. Despite their characteristics, these machines are not immune to failures. In this sense, breakage of the rotor bars (B...

Disentangling Noise from Images: A Flow-Based Image Denoising Neural Network.

Sensors (Basel, Switzerland)
The prevalent convolutional neural network (CNN)-based image denoising methods extract features of images to restore the clean ground truth, achieving high denoising accuracy. However, these methods may ignore the underlying distribution of clean ima...

Enhanced Classification of Dog Activities with Quaternion-Based Fusion Approach on High-Dimensional Raw Data from Wearable Sensors.

Sensors (Basel, Switzerland)
The employment of machine learning algorithms to the data provided by wearable movement sensors is one of the most common methods to detect pets' behaviors and monitor their well-being. However, defining features that lead to highly accurate behavior...

Machine learning for better prediction of seepage flow through embankment dams: Gaussian process regression versus SVR and RVM.

Environmental science and pollution research international
In the present study, three machine learning methods were applied for predicting seepage flow through embankment dams, namely (i) support vector regression (SVR), relevance vector machine (RVM), and Gaussian process regression (GPR). The three models...

Relating local connectivity and global dynamics in recurrent excitatory-inhibitory networks.

PLoS computational biology
How the connectivity of cortical networks determines the neural dynamics and the resulting computations is one of the key questions in neuroscience. Previous works have pursued two complementary approaches to quantify the structure in connectivity. O...

An application of deep dual convolutional neural network for enhanced medical image denoising.

Medical & biological engineering & computing
This work investigates the medical image denoising (MID) application of the dual denoising network (DudeNet) model for chest X-ray (CXR). The DudeNet model comprises four components: a feature extraction block with a sparse mechanism, an enhancement ...

Regularizing transformers with deep probabilistic layers.

Neural networks : the official journal of the International Neural Network Society
Language models (LM) have grown non-stop in the last decade, from sequence-to-sequence architectures to attention-based Transformers. However, regularization is not deeply studied in those structures. In this work, we use a Gaussian Mixture Variation...

Dual parallel net: A novel deep learning model for rectal tumor segmentation via CNN and transformer with Gaussian Mixture prior.

Journal of biomedical informatics
Segmentation of rectal cancerous regions from Magnetic Resonance (MR) images can help doctor define the extent of the rectal cancer and judge the severity of rectal cancer, so rectal tumor segmentation is crucial to improve the accuracy of rectal can...

DyVGRNN: DYnamic mixture Variational Graph Recurrent Neural Networks.

Neural networks : the official journal of the International Neural Network Society
Although graph representation learning has been studied extensively in static graph settings, dynamic graphs are less investigated in this context. This paper proposes a novel integrated variational framework called DYnamic mixture Variational Graph ...

Adversarial feature hybrid framework for steganography with shifted window local loss.

Neural networks : the official journal of the International Neural Network Society
Image steganography is a long-standing image security problem that aims at hiding information in cover images. In recent years, the application of deep learning to steganography has the tendency to outperform traditional methods. However, the vigorou...