Sample diversity, representation effectiveness and robust dictionary learning for face recognition
Conventional dictionary learning algorithms suffer from the following problems when applied
to face recognition. First, since in most face recognition applications there are only a limited …
to face recognition. First, since in most face recognition applications there are only a limited …
Robust, discriminative and comprehensive dictionary learning for face recognition
For sparse representation or sparse coding based image classification, the dictionary, which
is required to faithfully and robustly represent query images, plays an important role on its …
is required to faithfully and robustly represent query images, plays an important role on its …
Feature-enhanced speckle reduction via low-rank and space-angle continuity for circular SAR target recognition
L Chen, X Jiang, Z Li, X Liu… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
With the development of synthetic aperture radar (SAR) system, automatic target recognition
(ATR) has attracted wide attention in many decision-making tasks, in which an enhanced …
(ATR) has attracted wide attention in many decision-making tasks, in which an enhanced …
Spectral-difference low-rank representation learning for hyperspectral anomaly detection
Anomaly detection of a hyperspectral image without any prior information has attracted
much more attention in remote sensing image understanding and interpretation, which aims …
much more attention in remote sensing image understanding and interpretation, which aims …
A novel locally linear KNN method with applications to visual recognition
A locally linear K Nearest Neighbor (LLK) method is presented in this paper with
applications to robust visual recognition. Specifically, the concept of an ideal representation …
applications to robust visual recognition. Specifically, the concept of an ideal representation …
Undersampled face recognition via robust auxiliary dictionary learning
In this paper, we address the problem of robust face recognition with undersampled training
data. Given only one or few training images available per subject, we present a novel …
data. Given only one or few training images available per subject, we present a novel …
Noise-robust dictionary learning with slack block-diagonal structure for face recognition
Abstract Strict '0-1'block-diagonal structure has been widely used for learning structured
representation in face recognition problems. However, it is questionable and unreasonable …
representation in face recognition problems. However, it is questionable and unreasonable …
Image classification with tailored fine-grained dictionaries
In this paper, we propose a novel fine-grained dictionary learning method for image
classification. To learn a high-quality discriminative dictionary, three types of multispecific …
classification. To learn a high-quality discriminative dictionary, three types of multispecific …
Linearized kernel dictionary learning
In this paper, we present a new approach of incorporating kernels into dictionary learning.
The kernel K-SVD algorithm (KKSVD), which has been introduced recently, shows an …
The kernel K-SVD algorithm (KKSVD), which has been introduced recently, shows an …
Separation of fault characteristic impulses of flexible thin-wall bearing based on wavelet transform and correlated Gini index
Y Yu, X Zhao - Mechanical Systems and Signal Processing, 2024 - Elsevier
The flexible thin-wall bearing, characterized by different kinematic attributes and fault
characteristic frequency in comparison to rolling bearings, introduces a great challenge in …
characteristic frequency in comparison to rolling bearings, introduces a great challenge in …