AIMC Topic: Normal Distribution

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Mood State Detection in Handwritten Tasks Using PCA-mFCBF and Automated Machine Learning.

Sensors (Basel, Switzerland)
In this research, we analyse data obtained from sensors when a user handwrites or draws on a tablet to detect whether the user is in a specific mood state. First, we calculated the features based on the temporal, kinematic, statistical, spectral and ...

A General Gaussian Heatmap Label Assignment for Arbitrary-Oriented Object Detection.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Recently, many arbitrary-oriented object detection (AOOD) methods have been proposed and attracted widespread attention in many fields. However, most of them are based on anchor-boxes or standard Gaussian heatmaps. Such label assignment strategy may ...

LT-FS-ID: Log-Transformed Feature Learning and Feature-Scaling-Based Machine Learning Algorithms to Predict the -Barriers for Intrusion Detection Using Wireless Sensor Network.

Sensors (Basel, Switzerland)
The dramatic increase in the computational facilities integrated with the explainable machine learning algorithms allows us to do fast intrusion detection and prevention at border areas using Wireless Sensor Networks (WSNs). This study proposed a nov...

The Design of Adolescents' Physical Health Prediction System Based on Deep Reinforcement Learning.

Computational intelligence and neuroscience
According to the general recognition in the first half of the last century, hypertension was not considered a kind of disease, but was regarded as a compensatory response commonly seen in the elderly, and it would not occur to younger people. Because...

Boundary curvature guided programmable shape-morphing kirigami sheets.

Nature communications
Kirigami, a traditional paper cutting art, offers a promising strategy for 2D-to-3D shape morphing through cut-guided deformation. Existing kirigami designs for target 3D curved shapes rely on intricate cut patterns in thin sheets, making the inverse...

Deep learning identified glioblastoma subtypes based on internal genomic expression ranks.

BMC cancer
BACKGROUND: Glioblastoma (GBM) can be divided into subtypes according to their genomic features, including Proneural (PN), Neural (NE), Classical (CL) and Mesenchymal (ME). However, it is a difficult task to unify various genomic expression profiles ...

Fatigue Crack Evaluation with the Guided Wave-Convolutional Neural Network Ensemble and Differential Wavelet Spectrogram.

Sensors (Basel, Switzerland)
On-line fatigue crack evaluation is crucial for ensuring the structural safety and reducing the maintenance costs of safety-critical systems. Among structural health monitoring (SHM), guided wave (GW)-based SHM has been deemed as one of the most prom...

Visual Perceptual Quality Assessment Based on Blind Machine Learning Techniques.

Sensors (Basel, Switzerland)
This paper presents the construction of a new objective method for estimation of visual perceiving quality. The proposal provides an assessment of image quality without the need for a reference image or a specific distortion assumption. Two main proc...

Attention Autoencoder for Generative Latent Representational Learning in Anomaly Detection.

Sensors (Basel, Switzerland)
Today, accurate and automated abnormality diagnosis and identification have become of paramount importance as they are involved in many critical and life-saving scenarios. To accomplish such frontiers, we propose three artificial intelligence models ...

Fusion of Infrared and Visible Images Using Fast Global Smoothing Decomposition and Target-Enhanced Parallel Gaussian Fuzzy Logic.

Sensors (Basel, Switzerland)
As a powerful technique to merge complementary information of original images, infrared (IR) and visible image fusion approaches are widely used in surveillance, target detecting, tracking, and biological recognition, etc. In this paper, an efficient...