AIMC Topic: Neural Networks, Computer

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A neurodynamic approach to nonsmooth constrained pseudoconvex optimization problem.

Neural networks : the official journal of the International Neural Network Society
This paper presents a new neurodynamic approach for solving the constrained pseudoconvex optimization problem based on more general assumptions. The proposed neural network is equipped with a hard comparator function and a piecewise linear function, ...

Topic-informed neural approach for biomedical event extraction.

Artificial intelligence in medicine
As a crucial step of biological event extraction, event trigger identification has attracted much attention in recent years. Deep representation methods, which have the superiorities of less feature engineering and end-to-end training, show better pe...

Global collaboration through local interaction in competitive learning.

Neural networks : the official journal of the International Neural Network Society
Feature maps, that preserve the global topology of arbitrary datasets, can be formed by self-organizing competing agents. So far, it has been presumed that global interaction of agents is necessary for this process. We establish that this is not the ...

When Deep Learning Meets Cell Image Synthesis.

Cytometry. Part A : the journal of the International Society for Analytical Cytology

Control of speaking rate is achieved by switching between qualitatively distinct cognitive "gaits": Evidence from simulation.

Psychological review
That speakers can vary their speaking rate is evident, but how they accomplish this has hardly been studied. Consider this analogy: When walking, speed can be continuously increased, within limits, but to speed up further, humans must run. Are there ...

Broiler stunned state detection based on an improved fast region-based convolutional neural network algorithm.

Poultry science
An improved fast region-based convolutional neural network (RCNN) algorithm is proposed to improve the accuracy and efficiency of recognizing broilers in a stunned state. The algorithm recognizes 3 stunned state conditions: insufficiently stunned, mo...

Neural Network Ensembles for Sensor-Based Human Activity Recognition Within Smart Environments.

Sensors (Basel, Switzerland)
In this paper, we focus on data-driven approaches to human activity recognition (HAR). Data-driven approaches rely on good quality data during training, however, a shortage of high quality, large-scale, and accurately annotated HAR datasets exists fo...

Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network.

Scientific reports
Identification of genotypes is crucial for treatment of glioma. Here, we developed a method to predict tumor genotypes using a pretrained convolutional neural network (CNN) from magnetic resonance (MR) images and compared the accuracy to that of a di...

DeepFHR: intelligent prediction of fetal Acidemia using fetal heart rate signals based on convolutional neural network.

BMC medical informatics and decision making
BACKGROUND: Fetal heart rate (FHR) monitoring is a screening tool used by obstetricians to evaluate the fetal state. Because of the complexity and non-linearity, a visual interpretation of FHR signals using common guidelines usually results in signif...

Automatic identification of crossovers in cryo-EM images of murine amyloid protein A fibrils with machine learning.

Journal of microscopy
Detecting crossovers in cryo-electron microscopy images of protein fibrils is an important step towards determining the morphological composition of a sample. Currently, the crossover locations are picked by hand, which introduces errors and is a tim...