AIMC Topic: Principal Component Analysis

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Mutual Information-Driven Feature Reduction for Hyperspectral Image Classification.

Sensors (Basel, Switzerland)
A hyperspectral image (HSI), which contains a number of contiguous and narrow spectral wavelength bands, is a valuable source of data for ground cover examinations. Classification using the entire original HSI suffers from the "curse of dimensionalit...

Study on the classification and identification of various carbonate and sulfate mineral medicines based on Raman spectroscopy combined with PCA-SVM algorithm.

Analytical sciences : the international journal of the Japan Society for Analytical Chemistry
The efficacy of mineral medicines varies greatly between different origins. Therefore, investigating a method to quickly identify similar mineral medicines is meaningful. In this paper, a visual classification and identification model of Raman spectr...

The harmonium model and its unified system view of psychopathology: a validation study by means of a convolutional neural network.

Scientific reports
The harmonium model (HM) is a recent conceptualization of the unifying view of psychopathology, namely the idea of a general mechanism underpinning all mental disorders (the p factor). According to HM, psychopathology consists of a low dimensional Ph...

Classification of Gravity Matching Areas Using PSO-BP Neural Networks based on PCA and Satellite Altimetry Data over the Western Pacific.

Sensors (Basel, Switzerland)
For inertial navigation systems (INS), as one of the major methods for underwater navigation, errors diverge over time. With the development of geophysical navigation technology, gravity navigation has become an effective method of navigation. Signif...

Water consumption prediction and influencing factor analysis based on PCA-BP neural network in karst regions: a case study of Guizhou Province.

Environmental science and pollution research international
Water consumption prediction is an integral part of water resource planning and management. Constructing a highly precise water consumption prediction model is of great significance for promoting regional water resource planning and high-quality deve...

A Guided Tutorial on Modelling Human Event-Related Potentials with Recurrent Neural Networks.

Sensors (Basel, Switzerland)
In cognitive neuroscience research, computational models of event-related potentials (ERP) can provide a means of developing explanatory hypotheses for the observed waveforms. However, researchers trained in cognitive neurosciences may face technical...

Deep neural network-based structural health monitoring technique for real-time crack detection and localization using strain gauge sensors.

Scientific reports
Structural health monitoring (SHM) techniques often require a large number of sensors to evaluate and monitor the structural health. In this paper, we propose a deep neural network (DNN)-based SHM method for accurate crack detection and localization ...

Deep Learning Model for the Image Fusion and Accurate Classification of Remote Sensing Images.

Computational intelligence and neuroscience
Deep learning is widely used for the classification of images that have various attributes. Image data are used to extract colour, texture, form, and local features. These features are combined in feature-level image fusion to create a merged remote ...

A New Mixed-Gas-Detection Method Based on a Support Vector Machine Optimized by a Sparrow Search Algorithm.

Sensors (Basel, Switzerland)
To solve the problem of the low recognition rate of mixed gases and consider the phenomenon of low prediction accuracy when traditional gas-concentration-prediction methods deal with nonlinear data, this paper proposes a mixed-gas identification and ...

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...