AIMC Topic: Signal-To-Noise Ratio

Clear Filters Showing 721 to 730 of 953 articles

Deep(er) Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Animals successfully thrive in noisy environments with finite resources. The necessity to function with resource constraints has led evolution to design animal brains (and bodies) to be optimal in their use of computational power while being adaptabl...

Denoising of 3D magnetic resonance images with multi-channel residual learning of convolutional neural network.

Japanese journal of radiology
PURPOSE: To test if the proposed deep learning based denoising method denoising convolutional neural networks (DnCNN) with residual learning and multi-channel strategy can denoise three dimensional MR images with Rician noise robustly.

Threshold-Based Noise Detection and Reduction for Automatic Speech Recognition System in Human-Robot Interactions.

Sensors (Basel, Switzerland)
This work develops a speech recognition system that uses two procedures of proposed noise detection and combined noise reduction. The system can be used in applications that require interactive robots to recognize the contents of speech that includes...

A support vector machine approach for AF classification from a short single-lead ECG recording.

Physiological measurement
OBJECTIVE: In this paper, a support vector machine (SVM) approach using statistical features, P wave absence, spectrum features, and length-adaptive entropy are presented to classify ECG rhythms as four types: normal rhythm, atrial fibrillation (AF),...

Simultaneous single- and multi-contrast super-resolution for brain MRI images based on a convolutional neural network.

Computers in biology and medicine
In magnetic resonance imaging (MRI), the acquired images are usually not of high enough resolution due to constraints such as long sampling times and patient comfort. High-resolution MRI images can be obtained by super-resolution techniques, which ca...

Robust 3D point cloud registration based on bidirectional Maximum Correntropy Criterion.

PloS one
This paper presents a robust 3D point cloud registration algorithm based on bidirectional Maximum Correntropy Criterion (MCC). Comparing with traditional registration algorithm based on the mean square error (MSE), using the MCC is superior in dealin...

Design, verification and robotic application of a novel recurrent neural network for computing dynamic Sylvester equation.

Neural networks : the official journal of the International Neural Network Society
To solve dynamic Sylvester equation in the presence of additive noises, a novel recurrent neural network (NRNN) with finite-time convergence and excellent robustness is proposed and analyzed in this paper. As compared with the design process of Zhang...

Automated chest screening based on a hybrid model of transfer learning and convolutional sparse denoising autoencoder.

Biomedical engineering online
OBJECTIVE: In this paper, we aim to investigate the effect of computer-aided triage system, which is implemented for the health checkup of lung lesions involving tens of thousands of chest X-rays (CXRs) that are required for diagnosis. Therefore, hig...

Assessment of the generalization of learned image reconstruction and the potential for transfer learning.

Magnetic resonance in medicine
PURPOSE: Although deep learning has shown great promise for MR image reconstruction, an open question regarding the success of this approach is the robustness in the case of deviations between training and test data. The goal of this study is to asse...

Denoising Autoencoder Self-Organizing Map (DASOM).

Neural networks : the official journal of the International Neural Network Society
In this report, we address the question of combining nonlinearities of neurons into networks for modeling increasingly varying and progressively more complex functions. A fundamental approach is the use of higher-level representations devised by rest...