AIMC Topic: Neural Networks, Computer

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Rolling Bearing Fault Diagnosis Using Hybrid Neural Network with Principal Component Analysis.

Sensors (Basel, Switzerland)
With the rapid development of fault prognostics and health management (PHM) technology, more and more deep learning algorithms have been applied to the intelligent fault diagnosis of rolling bearings, and although all of them can achieve over 90% dia...

Zoom-In Neural Network Deep-Learning Model for Alzheimer's Disease Assessments.

Sensors (Basel, Switzerland)
Deep neural networks have been successfully applied to generate predictive patterns from medical and diagnostic data. This paper presents an approach for assessing persons with Alzheimer's disease (AD) mild cognitive impairment (MCI), compared with n...

Efficient Object Detection Based on Masking Semantic Segmentation Region for Lightweight Embedded Processors.

Sensors (Basel, Switzerland)
Because of the development of image processing using cameras and the subsequent development of artificial intelligence technology, various fields have begun to develop. However, it is difficult to implement an image processing algorithm that requires...

Machine Learning Techniques for Arousal Classification from Electrodermal Activity: A Systematic Review.

Sensors (Basel, Switzerland)
This article introduces a systematic review on arousal classification based on electrodermal activity (EDA) and machine learning (ML). From a first set of 284 articles searched for in six scientific databases, fifty-nine were finally selected accordi...

A New SCAE-MT Classification Model for Hyperspectral Remote Sensing Images.

Sensors (Basel, Switzerland)
Hyperspectral remote sensing images (HRSI) have the characteristics of foreign objects with the same spectrum. As it is difficult to label samples manually, the hyperspectral remote sensing images are understood to be typical "small sample" datasets....

GLSNN Network: A Multi-Scale Spatiotemporal Prediction Model for Urban Traffic Flow.

Sensors (Basel, Switzerland)
Traffic flow prediction is a key issue in intelligent transportation systems. The growing trend in data disclosure has created more potential sources for the input for predictive models, posing new challenges to the prediction of traffic flow in the ...

A Graph Neural Network Approach for the Analysis of siRNA-Target Biological Networks.

International journal of molecular sciences
Many biological systems are characterised by biological entities, as well as their relationships. These interaction networks can be modelled as graphs, with nodes representing bio-entities, such as molecules, and edges representing relations among th...

Automatic ovarian tumors recognition system based on ensemble convolutional neural network with ultrasound imaging.

BMC medical informatics and decision making
BACKGROUND: Upon the discovery of ovarian cysts, obstetricians, gynecologists, and ultrasound examiners must address the common clinical challenge of distinguishing between benign and malignant ovarian tumors. Numerous types of ovarian tumors exist, ...

Detection of K-complexes in EEG waveform images using faster R-CNN and deep transfer learning.

BMC medical informatics and decision making
BACKGROUND: The electroencephalography (EEG) signal carries important information about the electrical activity of the brain, which may reveal many pathologies. This information is carried in certain waveforms and events, one of which is the K-comple...

Multi-factor settlement prediction around foundation pit based on SSA-gradient descent model.

Scientific reports
With the rise of machine learning, a lot of excellent algorithms are used for settlement prediction. Backpropagation (BP) and Elman are two typical algorithms based on gradient descent, but their performance is greatly affected by the random selectio...