AIMC Topic: Neural Networks, Computer

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A theory of local learning, the learning channel, and the optimality of backpropagation.

Neural networks : the official journal of the International Neural Network Society
In a physical neural system, where storage and processing are intimately intertwined, the rules for adjusting the synaptic weights can only depend on variables that are available locally, such as the activity of the pre- and post-synaptic neurons, re...

Massively parallel WRNN reconstructors for spectrum recovery in astronomical photometrical surveys.

Neural networks : the official journal of the International Neural Network Society
The investigation of solar-like oscillations for probing star interiors has enjoyed a tremendous growth in the last decade. Once observations are over, the most notable difficulties in properly identifying the true oscillation frequencies of stars ar...

Identifying Important Attributes for Prognostic Prediction in Traumatic Brain Injury Patients. A Hybrid Method of Decision Tree and Neural Network.

Methods of information in medicine
BACKGROUND: Generally, traumatic brain injury (TBI) patients do not have a stable condition, particularly after the first week of TBI. Hence, indicating the attributes in prognosis through a prediction model is of utmost importance since it helps car...

Clustering of soybean genotypes via Ward-MLM and ANNs associated with mixed models.

Genetics and molecular research : GMR
The objectives of this study were to use mixed models to confirm the presence of genetic variability in 16 soybean genotypes, to compare clusters generated by artificial neural networks (ANNs) with those created by the Ward modified location model (M...

A prediction model of blood pressure for telemedicine.

Health informatics journal
This paper presents a new study based on a machine learning technique, specifically an artificial neural network, for predicting systolic blood pressure through the correlation of variables (age, BMI, exercise level, alcohol consumption level, smokin...

Boosting backpropagation algorithm by stimulus-sampling: Application in computer-aided medical diagnosis.

Journal of biomedical informatics
Neural networks (NNs), in general, and multi-layer perceptron (MLP), in particular, represent one of the most efficient classifiers among the machine learning (ML) algorithms. Inspired by the stimulus-sampling paradigm, it is plausible to assume that...

Global cluster synchronization in nonlinearly coupled community networks with heterogeneous coupling delays.

Neural networks : the official journal of the International Neural Network Society
This investigation establishes the global cluster synchronization of complex networks with a community structure based on an iterative approach. The units comprising the network are described by differential equations, and can be non-autonomous and i...

DeepFruits: A Fruit Detection System Using Deep Neural Networks.

Sensors (Basel, Switzerland)
This paper presents a novel approach to fruit detection using deep convolutional neural networks. The aim is to build an accurate, fast and reliable fruit detection system, which is a vital element of an autonomous agricultural robotic platform; it i...

Large scale deep learning for computer aided detection of mammographic lesions.

Medical image analysis
Recent advances in machine learning yielded new techniques to train deep neural networks, which resulted in highly successful applications in many pattern recognition tasks such as object detection and speech recognition. In this paper we provide a h...

Revealing disease-associated pathways by network integration of untargeted metabolomics.

Nature methods
Uncovering the molecular context of dysregulated metabolites is crucial to understand pathogenic pathways. However, their system-level analysis has been limited owing to challenges in global metabolite identification. Most metabolite features detecte...