AIMC Topic: Neural Networks, Computer

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Phase function estimation from a diffuse optical image via deep learning.

Physics in medicine and biology
The phase function is a key element of a light propagation model for Monte Carlo (MC) simulation, which is usually fitted with an analytic function with associated parameters. In recent years, machine learning methods were reported to estimate the pa...

Research on Application of Sports Training Performance Prediction Based on Convolutional Neural Network.

Computational and mathematical methods in medicine
In order to improve the prediction effect of sports training performance and improve the effect of sports training, this paper classifies the sports training image area, refines the image into different areas, finds suspicious areas, and completes th...

Hybrid Hypercube Optimization Search Algorithm and Multilayer Perceptron Neural Network for Medical Data Classification.

Computational intelligence and neuroscience
The hypercube optimization search (HOS) approach is a new efficient and robust metaheuristic algorithm that simulates the dove's movement in quest of new food sites in nature, utilizing hypercubes to depict the search zones. In medical informatics, t...

Empirical Analysis for Stock Price Prediction Using NARX Model with Exogenous Technical Indicators.

Computational intelligence and neuroscience
Stock price prediction is one of the major challenges for investors who participate in the stock markets. Therefore, different methods have been explored by practitioners and academicians to predict stock price movement. Artificial intelligence model...

Application of a Hybrid Model of Big Data and BP Network on Fault Diagnosis Strategy for Microgrid.

Computational intelligence and neuroscience
Aiming at the characteristics of timely transmission, rapid update, and large magnitude of microgrid data, based on the large data samples generated by microgrid operation, a fault diagnosis and analysis method of microgrid systems supported by big d...

A Unified Neural Network Framework for Extended Redundancy Analysis.

Psychometrika
Component-based approaches have been regarded as a tool for dimension reduction to predict outcomes from observed variables in regression applications. Extended redundancy analysis (ERA) is one such component-based approach which reduces predictors t...

New double decomposition deep learning methods for river water level forecasting.

The Science of the total environment
Forecasting river water levels or streamflow water levels (SWL) is vital to optimising the practical and sustainable use of available water resources. We propose a new deep learning hybrid model for SWL forecasting using convolutional neural networks...

GHNN: Graph Harmonic Neural Networks for semi-supervised graph-level classification.

Neural networks : the official journal of the International Neural Network Society
Graph classification aims to predict the property of the whole graph, which has attracted growing attention in the graph learning community. This problem has been extensively studied in the literature of both graph convolutional networks and graph ke...

Self-supervised Natural Image Reconstruction and Large-scale Semantic Classification from Brain Activity.

NeuroImage
Reconstructing natural images and decoding their semantic category from fMRI brain recordings is challenging. Acquiring sufficient pairs of images and their corresponding fMRI responses, which span the huge space of natural images, is prohibitive. We...