AIMC Topic: Neural Networks, Computer

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Prediction of persistent hemodynamic depression after carotid angioplasty and stenting using artificial neural network model.

Clinical neurology and neurosurgery
OBJECTIVES: To assess and compare predictive factors for persistent hemodynamic depression (PHD) after carotid artery angioplasty and stenting (CAS) using artificial neural network (ANN) and multiple logistic regression (MLR) or support vector machin...

Towards deep learning with segregated dendrites.

eLife
Deep learning has led to significant advances in artificial intelligence, in part, by adopting strategies motivated by neurophysiology. However, it is unclear whether deep learning could occur in the real brain. Here, we show that a deep learning alg...

A novel post-processing scheme for two-dimensional electrical impedance tomography based on artificial neural networks.

PloS one
OBJECTIVE: Electrical Impedance Tomography (EIT) is a powerful non-invasive technique for imaging applications. The goal is to estimate the electrical properties of living tissues by measuring the potential at the boundary of the domain. Being safe w...

Efficient Group-n Encoding and Decoding for Facial Age Estimation.

IEEE transactions on pattern analysis and machine intelligence
Different ages are closely related especially among the adjacent ages because aging is a slow and extremely non-stationary process with much randomness. To explore the relationship between the real age and its adjacent ages, an age group-n encoding (...

Joint Hand Detection and Rotation Estimation Using CNN.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Hand detection is essential for many hand related tasks, e.g., recovering hand pose and understanding gesture. However, hand detection in uncontrolled environments is challenging due to the flexibility of wrist joint and cluttered background. We prop...

Construction of a system using a deep learning algorithm to count cell numbers in nanoliter wells for viable single-cell experiments.

Scientific reports
For single-cell experiments, it is important to accurately count the number of viable cells in a nanoliter well. We used a deep learning-based convolutional neural network (CNN) on a large amount of digital data obtained as microscopic images. The tr...

Standard representation and unified stability analysis for dynamic artificial neural network models.

Neural networks : the official journal of the International Neural Network Society
An overview is provided of dynamic artificial neural network models (DANNs) for nonlinear dynamical system identification and control problems, and convex stability conditions are proposed that are less conservative than past results. The three most ...

Fixed-time stabilization of impulsive Cohen-Grossberg BAM neural networks.

Neural networks : the official journal of the International Neural Network Society
This article is concerned with the fixed-time stabilization for impulsive Cohen-Grossberg BAM neural networks via two different controllers. By using a novel constructive approach based on some comparison techniques for differential inequalities, an ...

Learning non-linear patch embeddings with neural networks for label fusion.

Medical image analysis
In brain structural segmentation, multi-atlas strategies are increasingly being used over single-atlas strategies because of their ability to fit a wider anatomical variability. Patch-based label fusion (PBLF) is a type of such multi-atlas approaches...

Nonlinear recurrent neural networks for finite-time solution of general time-varying linear matrix equations.

Neural networks : the official journal of the International Neural Network Society
In order to solve general time-varying linear matrix equations (LMEs) more efficiently, this paper proposes two nonlinear recurrent neural networks based on two nonlinear activation functions. According to Lyapunov theory, such two nonlinear recurren...