Cargando…
A Probabilistic Analysis of Sparse Coded Feature Pooling and Its Application for Image Retrieval
Feature coding and pooling as a key component of image retrieval have been widely studied over the past several years. Recently sparse coding with max-pooling is regarded as the state-of-the-art for image classification. However there is no comprehensive study concerning the application of sparse co...
Autores principales: | Zhang, Yunchao, Chen, Jing, Huang, Xiujie, Wang, Yongtian |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489107/ https://www.ncbi.nlm.nih.gov/pubmed/26132080 http://dx.doi.org/10.1371/journal.pone.0131721 |
Ejemplares similares
-
A Sparse Probabilistic Code Underlies the Limits of Behavioral Discrimination
por: Sriram, Balaji, et al.
Publicado: (2020) -
Phaseless Terahertz Coded-Aperture Imaging for Sparse Target Based on Phase Retrieval Algorithm
por: Peng, Long, et al.
Publicado: (2019) -
Sparse Coding Models Can Exhibit Decreasing Sparseness while Learning Sparse Codes for Natural Images
por: Zylberberg, Joel, et al.
Publicado: (2013) -
Categorizing biomedicine images using novel image features and sparse coding
representation
por: Sheng, Jianqiang, et al.
Publicado: (2013) -
Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval
por: Karisani, Payam, et al.
Publicado: (2018)