AIMC Topic: Neural Networks, Computer

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Medical Image Fusion Based on Sparse Representation and PCNN in NSCT Domain.

Computational and mathematical methods in medicine
The clinical assistant diagnosis has a high requirement for the visual effect of medical images. However, the low frequency subband coefficients obtained by the NSCT decomposition are not sparse, which is not conducive to maintaining the details of t...

The characteristic patterns of neuronal avalanches in mice under anesthesia and at rest: An investigation using constrained artificial neural networks.

PloS one
Local perturbations within complex dynamical systems can trigger cascade-like events that spread across significant portions of the system. Cascades of this type have been observed across a broad range of scales in the brain. Studies of these cascade...

Prediction of central neuropathic pain in spinal cord injury based on EEG classifier.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVES: To create a classifier based on electroencephalography (EEG) to identify spinal cord injured (SCI) participants at risk of developing central neuropathic pain (CNP) by comparing them with patients who had already developed pain and with a...

3D Tooth Segmentation and Labeling Using Deep Convolutional Neural Networks.

IEEE transactions on visualization and computer graphics
In this paper, we present a novel approach for 3D dental model segmentation via deep Convolutional Neural Networks (CNNs). Traditional geometry-based methods tend to receive undesirable results due to the complex appearance of human teeth (e.g., miss...

Recent developments of artificial intelligence in drying of fresh food: A review.

Critical reviews in food science and nutrition
Intellectualization is an important direction of drying development and artificial intelligence (AI) technologies have been widely used to solve problems of nonlinear function approximation, pattern detection, data interpretation, optimization, simul...

Adaptive detrending to accelerate convolutional gated recurrent unit training for contextual video recognition.

Neural networks : the official journal of the International Neural Network Society
Video image recognition has been extensively studied with rapid progress recently. However, most methods focus on short-term rather than long-term (contextual) video recognition. Convolutional recurrent neural networks (ConvRNNs) provide robust spati...

Fine-grained leukocyte classification with deep residual learning for microscopic images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Leukocyte classification and cytometry have wide applications in medical domain, previous researches usually exploit machine learning techniques to classify leukocytes automatically. However, constrained by the past developm...

Ω-Net (Omega-Net): Fully automatic, multi-view cardiac MR detection, orientation, and segmentation with deep neural networks.

Medical image analysis
Pixelwise segmentation of the left ventricular (LV) myocardium and the four cardiac chambers in 2-D steady state free precession (SSFP) cine sequences is an essential preprocessing step for a wide range of analyses. Variability in contrast, appearanc...

A Fungus Spores Dataset and a Convolutional Neural Network Based Approach for Fungus Detection.

IEEE transactions on nanobioscience
Fungus is enormously notorious for food, human health, and archives. Fungus sign and symptoms in medical science are non-specific and asymmetrical for extremely large areas resulting into a challenging task of fungal detection. Various traditional an...

Relationships Between the External and Internal Training Load in Professional Soccer: What Can We Learn From Machine Learning?

International journal of sports physiology and performance
PURPOSE: Machine learning may contribute to understanding the relationship between the external load and internal load in professional soccer. Therefore, the relationship between external load indicators (ELIs) and the rating of perceived exertion (R...