Class-wise dictionary learning for hyperspectral image classification

S Hao, W Wang, Y Yan, L Bruzzone - Neurocomputing, 2017 - Elsevier
In order to effectively exploit the intra-class and inter-class structure information, we propose
a new class-wise dictionary learning method for hyperspectral image classification. First, we …

Semi-supervised dictionary learning with label propagation for image classification

L Chen, M Yang - Computational Visual Media, 2017 - Springer
Sparse coding and supervised dictionary learning have rapidly developed in recent years,
and achieved impressive performance in image classification. However, there is usually a …

Exploiting spatial-temporal locality of tracking via structured dictionary learning

Y Sui, G Wang, L Zhang… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
In this paper, a novel spatial-temporal locality is proposed and unified via a discriminative
dictionary learning framework for visual tracking. By exploring the strong local correlations …

Automatic microaneurysms detection based on multifeature fusion dictionary learning

W Zhou, C Wu, D Chen, Z Wang, Y Yi… - … Methods in Medicine, 2017 - Wiley Online Library
Recently, microaneurysm (MA) detection has attracted a lot of attention in the medical image
processing community. Since MAs can be seen as the earliest lesions in diabetic …

Discriminative semi-supervised dictionary learning with entropy regularization for pattern classification

M Yang, L Chen - Proceedings of the AAAI Conference on Artificial …, 2017 - ojs.aaai.org
Dictionary learning has played an important role in the success of sparse representation,
which triggers the rapid developments of unsupervised and supervised dictionary learning …

Visual representation and classification by learning group sparse deep stacking network

J Li, H Chang, J Yang, W Luo… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Deep stacking networks (DSNs) have been successfully applied in classification tasks. Its
architecture builds upon blocks of simplified neural network modules (SNNM). The hidden …

Robust multi‐feature visual tracking via multi‐task kernel‐based sparse learning

B Kang, WP Zhu, D Liang - IET Image Processing, 2017 - Wiley Online Library
Feature selection and fusion is of crucial importance in multi‐feature visual tracking. This
study proposes a multi‐task kernel‐based sparse learning method for multi‐feature visual …

Joint distances by sparse representation and locality-constrained dictionary learning for robust leaf recognition

S Zeng, B Zhang, Y Du - Computers and Electronics in Agriculture, 2017 - Elsevier
Plant species recognition has been a difficult and important task in agriculture, where
computer techniques like image processing and pattern recognition can commendably …

Discriminative sparse representation for hyperspectral image classification: A semi-supervised perspective

Z Xue, P Du, H Su, S Zhou - Remote Sensing, 2017 - mdpi.com
This paper presents a novel semi-supervised joint dictionary learning (S 2 JDL) algorithm for
hyperspectral image classification. The algorithm jointly minimizes the reconstruction and …

Segment-oriented depiction and analysis for hyperspectral image data

J Yin, H Qv, X Luo, X Jia - IEEE Transactions on Geoscience …, 2017 - ieeexplore.ieee.org
A novel segment-oriented dictionary learning (SeODL) framework for hyperspectral image
(HSI) classification is proposed. Differing from existing HSI classification methods which …