AIMC Topic: Neural Networks, Computer

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Opening up the blackbox: an interpretable deep neural network-based classifier for cell-type specific enhancer predictions.

BMC systems biology
BACKGROUND: Gene expression is mediated by specialized cis-regulatory modules (CRMs), the most prominent of which are called enhancers. Early experiments indicated that enhancers located far from the gene promoters are often responsible for mediating...

Improving the ground reaction force prediction accuracy using one-axis plantar pressure: Expansion of input variable for neural network.

Journal of biomechanics
In this study, we describe a method to predict 6-axis ground reaction forces based solely on plantar pressure (PP) data obtained from insole type measurement devices free of space limitations. Because only vertical force is calculable from PP data, a...

Simbrain 3.0: A flexible, visually-oriented neural network simulator.

Neural networks : the official journal of the International Neural Network Society
Simbrain 3.0 is a software package for neural network design and analysis, which emphasizes flexibility (arbitrarily complex networks can be built using a suite of basic components) and a visually rich, intuitive interface. These features support bot...

A neural network-based method for spectral distortion correction in photon counting x-ray CT.

Physics in medicine and biology
Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the ot...

The effect of geographical indices on left ventricular structure in healthy Han Chinese population.

International journal of biometeorology
The left ventricular posterior wall thickness (LVPWT) and interventricular septum thickness (IVST) are generally regarded as the functional parts of the left ventricular (LV) structure. This paper aims to examine the effects of geographical indices o...

Teaching artificial intelligence to read electropherograms.

Forensic science international. Genetics
Electropherograms are produced in great numbers in forensic DNA laboratories as part of everyday criminal casework. Before the results of these electropherograms can be used they must be scrutinised by analysts to determine what the identified data t...

Unscented Kalman Filter-Trained Neural Networks for Slip Model Prediction.

PloS one
The purpose of this work is to investigate the accurate trajectory tracking control of a wheeled mobile robot (WMR) based on the slip model prediction. Generally, a nonholonomic WMR may increase the slippage risk, when traveling on outdoor unstructur...

Relating observability and compressed sensing of time-varying signals in recurrent linear networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, we study how the dynamics of recurrent networks, formulated as general dynamical systems, mediate the recovery of sparse, time-varying signals. Our formulation resembles the well-described problem of compressed sensing, but in a dynami...

Stability analysis of switched cellular neural networks: A mode-dependent average dwell time approach.

Neural networks : the official journal of the International Neural Network Society
This paper addresses the exponential stability of switched cellular neural networks by using the mode-dependent average dwell time (MDADT) approach. This method is quite different from the traditional average dwell time (ADT) method in permitting eac...