AIMC Topic: Neural Networks, Computer

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Design and Implementation of Opportunity Signal Perception Unit Based on Time-Frequency Representation and Convolutional Neural Network.

Sensors (Basel, Switzerland)
The traditional signal of opportunity (SOP) positioning system is equipped with dedicated receivers for each type of signal to ensure continuous signal perception. However, it causes a low equipment resources utilization and energy waste. With increa...

Multipath Lightweight Deep Network Using Randomly Selected Dilated Convolution.

Sensors (Basel, Switzerland)
Robot vision is an essential research field that enables machines to perform various tasks by classifying/detecting/segmenting objects as humans do. The classification accuracy of machine learning algorithms already exceeds that of a well-trained hum...

A deep learning model for identifying diabetic retinopathy using optical coherence tomography angiography.

Scientific reports
As the prevalence of diabetes increases, millions of people need to be screened for diabetic retinopathy (DR). Remarkable advances in technology have made it possible to use artificial intelligence to screen DR from retinal images with high accuracy ...

Direct pixel to pixel principal strain mapping from tagging MRI using end to end deep convolutional neural network (DeepStrain).

Scientific reports
Regional soft tissue mechanical strain offers crucial insights into tissue's mechanical function and vital indicators for different related disorders. Tagging magnetic resonance imaging (tMRI) has been the standard method for assessing the mechanical...

Application of PSO-based LSTM Neural Network for Outpatient Volume Prediction.

Journal of healthcare engineering
In order to study the construction method of long- and short-term memory neural network model, which is based on particle swarm optimization algorithm and its application in hospital outpatient management, we have selected historical data of outpatie...

The New Simulation of Quasiperiodic Wave, Periodic Wave, and Soliton Solutions of the KdV-mKdV Equation via a Deep Learning Method.

Computational intelligence and neuroscience
How to solve the numerical solution of nonlinear partial differential equations efficiently and conveniently has always been a difficult and meaningful problem. In this paper, the data-driven quasiperiodic wave, periodic wave, and soliton solutions o...

DAR-Net: Dense Attentional Residual Network for Vehicle Detection in Aerial Images.

Computational intelligence and neuroscience
With the rapid development of deep learning and the wide usage of Unmanned Aerial Vehicles (UAVs), CNN-based algorithms of vehicle detection in aerial images have been widely studied in the past several years. As a downstream task of the general obje...

Design of the Piano Score Recommendation Image Analysis System Based on the Big Data and Convolutional Neural Network.

Computational intelligence and neuroscience
In the era of big data, the problem of information overload is becoming more and more obvious. A piano music image analysis and recommendation system based on the CNN classifier and user preference is designed by using the convolutional neural networ...

Weather forecasting based on data-driven and physics-informed reservoir computing models.

Environmental science and pollution research international
In response to the growing demand for the global energy supply chain, wind power has become an important research subject among studies in the advancement of renewable energy sources. The major concern is the stochastic volatility of weather conditio...

A deep learning approach in automated detection of schizophrenia using scalogram images of EEG signals.

Physical and engineering sciences in medicine
This study presents a method with high accuracy performance that aims to automatically detect schizophrenia (SZ) from electroencephalography (EEG) records. Unlike related literature studies using traditional machine learning algorithms, the features ...