AIMC Topic: Support Vector Machine

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A Neural Network Model for Color Element Data Analysis for Urban Spatial Environment.

Computational intelligence and neuroscience
In this paper, a CNN model for color element data analysis of the urban spatial environment is constructed through an in-depth study of color element data analysis. This paper investigates a high-order structure formed by a few nodes; it proposes a m...

A data-centric weak supervised learning for highway traffic incident detection.

Accident; analysis and prevention
Using the data from loop detector sensors for near-real-time detection of traffic incidents on highways is crucial to averting major traffic congestion. While recent supervised machine learning methods offer solutions to incident detection by leverag...

Aggregation Strategy on Federated Machine Learning Algorithm for Collaborative Predictive Maintenance.

Sensors (Basel, Switzerland)
Industry 4.0 lets the industry build compact, precise, and connected assets and also has made modern industrial assets a massive source of data that can be used in process optimization, defining product quality, and predictive maintenance (PM). Large...

CNN-XGBoost fusion-based affective state recognition using EEG spectrogram image analysis.

Scientific reports
Recognizing emotional state of human using brain signal is an active research domain with several open challenges. In this research, we propose a signal spectrogram image based CNN-XGBoost fusion method for recognising three dimensions of emotion, na...

Evaluation of College English Teaching Quality Based on Improved BT-SVM Algorithm.

Computational intelligence and neuroscience
With the development of teaching evaluation program, colleges and universities have reformed according to the actual situation of the school. With the development of evaluation activities, many universities are eager to establish their own teaching q...

Comparison of machine learning methods for the detection of focal cortical dysplasia lesions: decision tree, support vector machine and artificial neural network.

Neurological research
BACKGROUND: Accurate classification of focal cortical dysplasia (FCD) has been challenging due to the problematic visual detection in magnetic resonance imaging (MRI). Hence, recently, there has been a necessity for employing new techniques to solve ...

The Significance of Software Engineering to Forecast the Public Health Issues: A Case of Saudi Arabia.

Frontiers in public health
In the recent years, public health has become a core issue addressed by researchers. However, because of our limited knowledge, studies mainly focus on the causes of public health issues. On the contrary, this study provides forecasts of public healt...

Interstitial lung disease detection using template matching combined sparse coding and blended multi class support vector machine.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Interstitial lung disease (ILD), representing a collection of disorders, is considered to be the deadliest one, which increases the mortality rate of humans. In this paper, an automated scheme for detection and classification of ILD patterns is prese...

Combining imaging flow cytometry and machine learning for high-throughput schistocyte quantification: A SVM classifier development and external validation cohort.

EBioMedicine
BACKGROUND: Schistocyte counts are a cornerstone of the diagnosis of thrombotic microangiopathy syndrome (TMA). Their manual quantification is complex and alternative automated methods suffer from pitfalls that limit their use. We report a method com...

Flow Pattern Identification of Oil-Water Two-Phase Flow Based on SVM Using Ultrasonic Testing Method.

Sensors (Basel, Switzerland)
A flow pattern identification method combining ultrasonic transmission attenuation with an ultrasonic reflection echo is proposed for oil-water two-phase flow in horizontal pipelines. Based on the finite element method, two-dimensional geometric simu...