☆ 4.7 Article

Exponential Graph Regularized Non-Negative Low-Rank Factorization for Robust Latent Representation

MATHEMATICS (2022)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Computer Science, Artificial Intelligence

Low-rank 2D local discriminant graph embedding for robust image feature extraction

Minghua Wan et al.

Summary: This paper introduces the incorporation of low-rank into the 2DLPP algorithm and proposes a new feature extraction algorithm, LR-2DLDGE, to address the limitations of the traditional 2DLPP algorithm in real-world applications. LR-2DLDGE algorithm combines graph embedding, low-rank learning, and L(1)-norm constraint to achieve improved effectiveness and robustness, as demonstrated through extensive experimental results.

PATTERN RECOGNITION (2023)

添加到收藏夹

Article Mathematics

A New Bilinear Supervised Neighborhood Discrete Discriminant Hashing

Xueyu Chen et al.

Summary: This paper proposes a new hashing algorithm, BNDDH, which extracts image features by constructing neighborhood graphs and using bilinear projection. Experimental results demonstrate that the proposed algorithm outperforms traditional algorithms in terms of different feature types.

MATHEMATICS (2022)

添加到收藏夹

Article Computer Science, Information Systems

A new weakly supervised discrete discriminant hashing for robust data representation

Minghua Wana et al.

Summary: This paper presents a new weakly supervised discrete discriminant hashing (WDDH) algorithm, which ensures a more effective representation of data and better retrieval of information by considering the nearest neighbour relationship between samples and constructing new neighbourhood graphs.

INFORMATION SCIENCES (2022)

添加到收藏夹

Review Engineering, Electrical & Electronic

Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review

Xin-Ru Feng et al.

Summary: This article provides a comprehensive survey of NMF-based methods for hyperspectral unmixing. It explores how to improve NMF by utilizing the spectral, spatial, and structural information of hyperspectral images. The study categorizes the development directions into constrained NMF, structured NMF, and generalized NMF, and conducts experiments to demonstrate the effectiveness of associated algorithms. The article concludes with possible future directions for the development of hyperspectral unmixing.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2022)

添加到收藏夹

Article Health Care Sciences & Services

Small sample sizes: A big data problem in high-dimensional data analysis

Frank Konietschke et al.

Summary: This paper discusses the applicability of max t-test-type statistics in high-dimensional designs with small sample sizes and presents a randomization-based approach to approximate the distribution of the maximum statistic. Extensive simulation studies confirm that the new method is particularly suitable for analyzing data sets with small sample sizes. A real data set illustrates the application of the methods.

STATISTICAL METHODS IN MEDICAL RESEARCH (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Low-rank adaptive graph emb e dding for unsupervise d feature extraction

Jianglin Lu et al.

Summary: The LRAGE method performs subspace learning and adaptive probabilistic neighborhood graph embedding based on reconstruction error minimization. It explores the underlying correlation structure of data and learns more informative projection through low-rank constraint and L2, 1-norm penalty regularization. Comparisons with similar models on synthetic and real-world data sets demonstrate the superiority of LRAGE.

PATTERN RECOGNITION (2021)

添加到收藏夹

Article Computer Science, Information Systems

Sparse fuzzy two-dimensional discriminant local preserving projection (SF2DDLPP) for robust image feature extraction

Minghua Wan et al.

Summary: The study introduces a new elastic feature extraction algorithm called SF2DDLPP to address the issues encountered in the 2DDLPP algorithm. By calculating the membership matrix using FKNN and developing two theorems to solve generalized eigenfunctions, the optimal sparse fuzzy 2D discriminant projection matrix is regressed.

INFORMATION SCIENCES (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

A survey: Deep learning for hyperspectral image classification with few labeled samples

Sen Jia et al.

Summary: With the advancement of deep learning technology, there is a growing focus on building deep learning models for HSI classification with few labeled samples, utilizing methods such as transfer learning, active learning, and few-shot learning. The results of the research indicate that the fusion of deep learning methods and related techniques can effectively address the issues of small-sample sets in HSI classification.

NEUROCOMPUTING (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Novel Proximal Gradient Methods for Nonnegative Matrix Factorization with Sparsity Constraints

Marc Teboulle et al.

SIAM JOURNAL ON IMAGING SCIENCES (2020)

添加到收藏夹

Article Computer Science, Information Systems

Low-rank nonnegative matrix factorization on Stiefel manifold

Ping He et al.

INFORMATION SCIENCES (2020)

添加到收藏夹

Article Geochemistry & Geophysics

Dimensionality Reduction With Enhanced Hybrid-Graph Discriminant Learning for Hyperspectral Image Classification

Fulin Luo et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2020)

添加到收藏夹

Review Computer Science, Artificial Intelligence

A review on the application of structured sparse representation at image annotation

Vafa Maihami et al.

ARTIFICIAL INTELLIGENCE REVIEW (2017)

添加到收藏夹

Article Computer Science, Theory & Methods

Local graph embedding based on maximum margin criterion via fuzzy set

Minghua Wan et al.

FUZZY SETS AND SYSTEMS (2017)

添加到收藏夹

Article Engineering, Electrical & Electronic

Novel feature extraction method for cough detection using NMF

Mingyu You et al.

IET SIGNAL PROCESSING (2017)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Linear discriminant analysis for the small sample size problem: an overview

Alok Sharma et al.

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS (2015)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Image clustering by hyper-graph regularized non-negative matrix factorization

Kun Zeng et al.

NEUROCOMPUTING (2014)

添加到收藏夹

Article Biochemistry & Molecular Biology

A collaborative framework for 3D alignment and classification of heterogeneous subvolumes in cryo-electron tomography

Oleg Kuybeda et al.

JOURNAL OF STRUCTURAL BIOLOGY (2013)

添加到收藏夹

Review Neurosciences

How Does the Brain Solve Visual Object Recognition?

James J. DiCarlo et al.

NEURON (2012)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Exponential locality preserving projections for small sample size problem

Su-Jing Wang et al.

NEUROCOMPUTING (2011)

添加到收藏夹

Article Mathematics, Applied

FAST NONNEGATIVE MATRIX FACTORIZATION: AN ACTIVE-SET-LIKE METHOD AND COMPARISONS

Jingu Kim et al.

SIAM JOURNAL ON SCIENTIFIC COMPUTING (2011)

添加到收藏夹

Article Mathematics, Applied

A SINGULAR VALUE THRESHOLDING ALGORITHM FOR MATRIX COMPLETION

Jian-Feng Cai et al.

SIAM JOURNAL ON OPTIMIZATION (2010)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Algorithms and applications for approximate nonnegative matrix factorization

Michael W. Berry et al.

COMPUTATIONAL STATISTICS & DATA ANALYSIS (2007)

添加到收藏夹

Article Computer Science, Artificial Intelligence

PCA versus LDA

AM Martìnez et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2001)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Independent component analysis:: algorithms and applications

A Hyvärinen et al.

NEURAL NETWORKS (2000)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.