Feature extraction for hyperspectral imagery: The evolution from shallow to deep: Overview and toolbox

B Rasti, D Hong, R Hang, P Ghamisi… - … and Remote Sensing …, 2020 - ieeexplore.ieee.org
Hyperspectral images (HSIs) provide detailed spectral information through hundreds of
(narrow) spectral channels (also known as dimensionality or bands), which can be used to …

A survey of sparse representation: algorithms and applications

Z Zhang, Y Xu, J Yang, X Li, D Zhang - IEEE access, 2015 - ieeexplore.ieee.org
Sparse representation has attracted much attention from researchers in fields of signal
processing, image processing, computer vision, and pattern recognition. Sparse …

Deep spatial feature reconstruction for partial person re-identification: Alignment-free approach

L He, J Liang, H Li, Z Sun - Proceedings of the IEEE …, 2018 - openaccess.thecvf.com
Partial person re-identification (re-id) is a challenging problem, where only a partial
observation of a person image is available for matching. However, few studies have offered …

Face feature extraction: a complete review

H Wang, J Hu, W Deng - IEEE Access, 2017 - ieeexplore.ieee.org
Feature extraction is vital for face recognition. In this paper, we focus on the general feature
extraction framework for robust face recognition. We collect about 300 papers regarding face …

Sparse representation or collaborative representation: Which helps face recognition?

L Zhang, M Yang, X Feng - 2011 International conference on …, 2011 - ieeexplore.ieee.org
As a recently proposed technique, sparse representation based classification (SRC) has
been widely used for face recognition (FR). SRC first codes a testing sample as a sparse …

Click prediction for web image reranking using multimodal sparse coding

J Yu, Y Rui, D Tao - IEEE transactions on image processing, 2014 - ieeexplore.ieee.org
Image reranking is effective for improving the performance of a text-based image search.
However, existing reranking algorithms are limited for two main reasons: 1) the textual meta …

MobileNetV2 model for image classification

K Dong, C Zhou, Y Ruan, Y Li - 2020 2nd International …, 2020 - ieeexplore.ieee.org
Machine learning has been increasingly prevailing all over the world, especially in the
computer vision field. This paper mainly focused on the performance of MobileNetV2 model …

Hyperspectral image classification via kernel sparse representation

Y Chen, NM Nasrabadi, TD Tran - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
In this paper, a novel nonlinear technique for hyperspectral image (HSI) classification is
proposed. Our approach relies on sparsely representing a test sample in terms of all of the …

Real-time human action recognition based on depth motion maps

C Chen, K Liu, N Kehtarnavaz - Journal of real-time image processing, 2016 - Springer
This paper presents a human action recognition method by using depth motion maps
(DMMs). Each depth frame in a depth video sequence is projected onto three orthogonal …

Laplacian sparse coding, hypergraph laplacian sparse coding, and applications

S Gao, IWH Tsang, LT Chia - IEEE Transactions on Pattern …, 2012 - ieeexplore.ieee.org
Sparse coding exhibits good performance in many computer vision applications. However,
due to the overcomplete codebook and the independent coding process, the locality and the …