Annular Spatial Pyramid Mapping and Feature Fusion-Based Image Coding Representation and Classification
Conventional image classification models commonly adopt a single feature vector to represent informative contents. However, a single image feature system can hardly extract the entirety of the information contained in images, and traditional encoding methods have a large loss of feature information....
Main Authors: | Mengxi Xu, Yingshu Lu, Xiaobin Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2020-01-01
|
Series: | Wireless Communications and Mobile Computing |
Online Access: | http://dx.doi.org/10.1155/2020/8838454 |
Similar Items
-
An Enhancement to the Spatial Pyramid Matching for Image Classification and Retrieval
by: Priyabrata Karmakar, et al.
Published: (2020-01-01) -
Weighted Spatial Pyramid Matching Collaborative Representation for Remote-Sensing-Image Scene Classification
by: Bao-Di Liu, et al.
Published: (2019-03-01) -
Scale Voting With Pyramidal Feature Fusion Network for Person Search
by: Zheran Hong, et al.
Published: (2019-01-01) -
A Lightweight Spectral–Spatial Feature Extraction and Fusion Network for Hyperspectral Image Classification
by: Linlin Chen, et al.
Published: (2020-04-01) -
Multi-pyramid image spatial structure based on coarse-to-fine pyramid and scale space
by: Jiucheng Xu, et al.
Published: (2018-12-01)