Deep Neural Network Structured Sparse Coding for Online Processing
Sparse coding, which aims at finding appropriate sparse representations of data with an overcomplete dictionary set, has become a mature class of methods with good efficiency in various areas, but it faces limitations in immediate processing such as real-time video denoising. Unsupervised deep neura...
Main Authors: | Haoli Zhao, Shuxue Ding, Xiang Li, Huakun Huang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2018-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8542719/ |
Similar Items
-
An Accurate and Efficient Device-Free Localization Approach Based on Sparse Coding in Subspace
by: Huakun Huang, et al.
Published: (2018-01-01) -
Fast Approximation for Sparse Coding with Applications to Object Recognition
by: Zhenzhen Sun, et al.
Published: (2021-02-01) -
Fast Sparse Coding for Range Data Denoising with Sparse Ridges Constraint
by: Zhi Gao, et al.
Published: (2018-05-01) -
Sparse coding of pathology slides compared to transfer learning with deep neural networks
by: Will Fischer, et al.
Published: (2018-12-01) -
Hyperspectral Image Denoising Based on Spectral Dictionary Learning and Sparse Coding
by: Xiaorui Song, et al.
Published: (2019-01-01)