Results 11 to 20 of about 9,222 (301)

Unsupervised Deep Embedded Clustering for High-Dimensional Visual Features of Fashion Images

Applied Sciences, 2023
Fashion image clustering is the key to fashion retrieval, forecasting, and recommendation applications. Manual labeling-based clustering is both time-consuming and less accurate.
Umar Subhan Malhi, Junfeng Zhou, Cairong Yan, Abdur Rasool, Shahbaz Siddeeq, Ming Du   +5 more
doaj   +1 more source

Mining pure, strict epistatic interactions from high-dimensional datasets: ameliorating the curse of dimensionality. [PDF]

PLoS One, 2012
Jiang X, Neapolitan RE.
europepmc   +3 more sources

Support Vector Machine – Recursive Feature Elimination for Feature Selection on Multi-omics Lung Cancer Data

Progress in Microbes and Molecular Biology, 2023
Biological data obtained from sequencing technologies is growing exponentially. Multi-omics data is one of the biological data that exhibits high dimensionality, or more commonly known as the curse of dimensionality.
Nuraina Syaza Azman, Azurah A Samah, Ji Tong Lin, Hairudin Abdul Majid, Zuraini Ali Shah, Nies Hui Wen, Chan Weng Howe   +6 more
doaj   +1 more source

A model-based clustering via mixture of hierarchical models with covariate adjustment for detecting differentially expressed genes from paired design

BMC Bioinformatics, 2023
The causes of many complex human diseases are still largely unknown. Genetics plays an important role in uncovering the molecular mechanisms of complex human diseases.
Yixin Zhang, Wei Liu, Weiliang Qiu
doaj   +1 more source

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, Saurabh Bilgaiyan, Bhabani Shankar Prasad Mishra, Satchidananda Dehuri, Ashish Ghosh   +4 more
doaj   +1 more source

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, Mehdi Mokhtarzade, Behnam Asghari Beirami   +2 more
doaj   +1 more source

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, Suling Liang, Lizhi Xu, Wei Song, Dexing Wang, Dongmei Huang   +5 more
doaj   +1 more source

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, Muhammad Amir Raza, Darakhshan Ara, Sohrab Mirsaeidi, Aamir Ali, Ghulam Abbas, Muhammad Shahid, Ezzeddine Touti, Amr Yousef, Amr Yousef, Mounir Bouzguenda   +10 more
doaj   +1 more source

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, Emiliano Casalicchio, Stefano Iannucci, Matteo Lucantonio, Sudip Mittal, Damodar Panigrahi, Andrea Silvi   +6 more
doaj   +1 more source

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, Xiaoheng Tan, Yongming Li, Pin Wang   +3 more
doaj   +1 more source