Yes, sparse-coding-based methods are still important in the field of super-resolution, although their significance has evolved over time. Sparse coding has been a crucial component in the development of super-resolution algorithms, and it provided a solid foundation for later methods. It essentially...
sparse coding.This paper analyzes the assumptions of sparse coding and provides the bounds of reconstruction error for two sparse coding methods which are widely used.Based on this analysis,the performance of the two methods under different conditions are compared.The results show that the performance...
4.1.3 Sparse coding methods Sparse coding proposed in Olshausen and Field (1997) provides a means to reduce sensor data dimension and represent them as an efficient linear combination of basis vectors. Due to the efficient data representation ability of sparse coding, a number of studies have use...
基于互补学习系统(Complementary Learning Systems,简称CLS)理论,提出了在DNNs中模仿大脑中不同记忆系统之间相互作用的想法。 本文提出了SCoMMER(Sparse Coding in a Multi-Memory Experience Replay mechanism)方法,其结合了稀疏编码和多记忆系统体验回放机制的方法,用于提高DNNs在持续学习任务中的表现。下图给出了SCoMMER...
Edgar Roman-Rangel, Jean-Marc Odobez, Daniel Gatica- Perez, "Assessing Sparse Coding Methods for Contextual Shape Indexing of Maya Hieroglyphs", Journal of Multimedia, vol. 7, no. 2, pp. 179-192, 2012.Edgar Roman-Rangel, Jean-Marc Odobez, and Daniel Gatica-Perez. 2012. Assessing Sparse ...
学术范收录的Conference Sparse Spatial Coding: A novel approach for efficient and accurate object recognition,目前已有全文资源,进入学术范阅读全文,查看参考文献与引证文献,参与文献内容讨论。学术范是一个在线学术交流社区,收录论文、作者、研究机构等信息,是
while sparse coding based methods mainly use hand-crafted features, which may not be optimal for video representation. For encoding-decoding neural networks based methods, 1) they merely concentrate on the (multi-) frame reconstruction errors in the pixel level, and ignore the high-level and sema...
However, due to the lack of effective modeling methods, how the simultaneously recorded LFP can inform us about the brain dynamics remains a general challenge. In this paper, we propose a novel sparse coding based method to investigate brain dynamics of freely-behaving mice from the perspective ...
Efficient ADMM-based Algorithms for Convolutional Sparse Coding Convolutional sparse coding improves on the standard sparse approximation by incorporating a global shift-invariant model. The most efficient convolutional sparse coding methods are based on the alternating direction method of multiplier... FG ...
However, the traditional sparse coding based methods fail to consider the accurate prediction performance of the sparse representation. It has been demonstrated that accurate prediction of the representation is of prime importance for linear regression model, which can improve the learning performance [21...