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Data Preprocessing
It is essential to extract useful knowledge from data for decision-making. However, the entire data is not always processing ready. It may contain...
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Enhancing visual clarity in hazy media: a comprehensive approach through preprocessing and feature fusion attention-based dehazing
Particles in the atmosphere, such as dust and smoke, can cause visual clarity problems in both images and videos. Haze is the result of the...
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A score-based preprocessing technique for class imbalance problems
In classification, one of the common problems is the class imbalance problem. This phenomenon that is growing significance emerges in most real...
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Streamflow prediction in mountainous region using new machine learning and data preprocessing methods: a case study
Accurate streamflow estimation is crucial for proper water management for irrigation, hydropower, drinking and industrial purposes. The main aim of...
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A Robust Preprocessing Method for Measuring Image Visual Quality Using Log-Polar FFT Features
To register two images, existing methods normally estimate the parameters of an affine transform, and then perform an inverse affine transform to the...
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Classification of Heart Diseases Using Logistic Regression with Various Preprocessing Techniques
Machine learning (ML) based heart disease prediction has emerged as a crucial and fruitful field of study and application. They are used to analyze...
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QRCP-based preprocessing for illumination invariant measure under severe illumination variations
The previous illumination invariant measure performs unsatisfactorily under severe illumination variations, since severe illumination variations...
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A hybrid-driven remaining useful life prediction method combining asymmetric dual-channel autoencoder and nonlinear Wiener process
Remaining Useful Life (RUL) prediction is an essential aspect of Prognostics and Health Management (PHM), facilitating the assessment of mechanical...
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Hybrid time-spatial video saliency detection method to enhance human action recognition systems
Since digital media has become increasingly popular, video processing has expanded in recent years. Video processing systems require high levels of...
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A New Preprocessing Method for Measuring Image Visual Quality Robust to Rotation and Spatial Shifts
Measuring the visual quality of an image is an extremely important task in computer vision. In this paper, we perform 2D fast Fourier transform (FFT)...
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Comparison Analysis on Techniques of Preprocessing Imbalanced Data for Symbolic Regression
Symbolic regression is an important research field which aims to find a symbolic function to fit a given data set. Since real-world data sets usually...
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MICAR: nonlinear association rule mining based on maximal information coefficient
Association rule mining (ARM) is an important research issue in data mining and knowledge discovery. Existing ARM methods cannot discover nonlinear...
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An empirical study of preprocessing techniques with convolutional neural networks for accurate detection of chronic ocular diseases using fundus images
Chronic Ocular Diseases (COD) such as myopia, diabetic retinopathy, age-related macular degeneration, glaucoma, and cataract can affect the eye and...
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A novel hybrid hunger games algorithm for intrusion detection systems based on nonlinear regression modeling
Along with the advancement of online platforms and significant growth in Internet usage, various threats and cyber-attacks have been emerging and...
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A deep learning-based nonlinear ensemble approach with biphasic feature selection for multivariate exchange rate forecasting
Exchange rate prediction is a challenging task for investors and policymakers due to its nonstationary and nonlinear characteristics. This study...
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A comprehensive comparison study of ML models for multistage APT detection: focus on data preprocessing and resampling
Advanced persistent threats (APTs) present a significant cybersecurity challenge, necessitating innovative detection methods. This study stands out...
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The Effectiveness of Using AutoML in Electricity Theft Detection: The Impact of Data Preprocessing and Balancing Techniques
Electricity theft is a significant threat to the economy and society’s security. Machine learning models are applied to consumption data obtained...
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Using nonlinear analysis and neural network to classify bipolar I disorder electroencephalogram signals from normal electroencephalograms
Bipolar I disorder is a severe neuropsychiatric illness that affects many people around the world. Early diagnosis of adolescents with bipolar I...
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Efficient Local Search for Nonlinear Real Arithmetic
Local search has recently been applied to SMT problems over various arithmetic theories. Among these, nonlinear real arithmetic poses special...
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Research on variational optical flow method for rockfall monitoring
Rockfall is a global mountain disaster problem, which has the characteristics of wide distribution, strong randomness, and inconspicuousness. The...
