A feature extraction method based on spectral segmentation and integration of hyperspectral images
International Journal of Applied Earth Observations and Geoinformation, 2020 In response to the curse of dimensionality in hyperspectral images (HSIs), to date, numerous dimensionality reduction methods have been proposed among which the feature extraction (FE) methods are of particular interest.
Sayyed Hamed Alizadeh Moghaddam +2 more
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Dimensionality reduction method for hyperspectral image analysis based on rough set theory
European Journal of Remote Sensing, 2020 High-dimensional features often cause computational complexity and dimensionality curse. Feature selection and feature extraction are the two mainstream methods for dimensionality reduction.
Zhenhua Wang +5 more
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Genetically Optimized UFLANN for Uncovering Clusters
IEEE Access, 2023 In this work, we present a novel clustering approach which is inheriting the best characteristics of Unsupervised Functional Link Artificial Neural Network (UFLANN) and Genetic Algorithms (GAs) for uncovering clusters embedded in dataset represented ...
Himanshu Dutta +4 more
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A deep learning technique Alexnet to detect electricity theft in smart grids
Frontiers in Energy Research, 2023 Electricity theft (ET), which endangers public safety, creates a problem with the regular operation of grid infrastructure and increases revenue losses. Numerous machine learning, deep learning, and mathematical-based algorithms are available to find ET.
Nitasha Khan +10 more
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Weighted Local Discriminant Preservation Projection Ensemble Algorithm With Embedded Micro-Noise
IEEE Access, 2019 High-dimensional data often cause the “curse of dimensionality” in data processing. Dimensionality reduction can effectively solve the curse of dimensionality and has been widely used in high-dimensional data processing.
Yuchuan Liu +3 more
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irs-partition: An Intrusion Response System utilizing Deep Q-Networks and system partitions
SoftwareX, 2022 Intrusion Response is a relatively new field of research. Recent approaches for the creation of Intrusion Response Systems (IRSs) use Reinforcement Learning (RL) as a primary technique for the optimal or near-optimal selection of the proper ...
Valeria Cardellini +6 more
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An Investigation into the Relationship between Curse of Dimensionality and Dunning-Kruger Effect
Sakarya University Journal of Computer and Information Sciences, 2020 This study addresses a novel perspective for analyzing the source of confidence in human behavior. The concept of confidence was examined via the relationship between two phenomena in the area of machine learning and psychology, namely the Dunning-Kruger
Dr. Mehmet Cem Çatalbaş
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Detecting disease-associated genomic outcomes using constrained mixture of Bayesian hierarchical models for paired data. [PDF]
PLoS ONE, 2017 Detecting disease-associated genomic outcomes is one of the key steps in precision medicine research. Cutting-edge high-throughput technologies enable researchers to unbiasedly test if genomic outcomes are associated with disease of interest.
Yunfeng Li +6 more
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A Survey on Dimensionality Reduction Techniques for Time-Series Data
IEEE Access, 2023 Data analysis in modern times involves working with large volumes of data, including time-series data. This type of data is characterized by its high dimensionality, enormous volume, and the presence of both noise and redundant features.
Mohsena Ashraf +6 more
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Neuro-dynamic Programming to Optimal Control of a Biotechnological Process [PDF]
International Journal BioautomationDynamic programming (DP) is an elegant way to solve problems related to optimization and optimal control of processes. DP, however, has one major drawback, namely the “curse of dimensionality”.
Tatiana Ilkova, Mitko Petrov
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