Efficient temporal sequence comparison and classification using gram matrix embeddings on a riemannian manifold

X Zhang, Y Wang, M Gou… - Proceedings of the …, 2016 - openaccess.thecvf.com
In this paper we propose a new framework to compare and classify temporal sequences.
The proposed approach captures the underlying dynamics of the data while avoiding …
被引用次数：116 相关文章

Efficient Temporal Sequence Comparison and Classification Using Gram Matrix Embeddings on a Riemannian Manifold

X Zhang, Y Wang, M Gou, M Sznaier… - Proceedings of the …, 2016 - cv-foundation.org
In this paper we propose a new framework to compare and classify temporal sequences.
The proposed approach captures the underlying dynamics of the data while avoiding …

Efficient Temporal Sequence Comparison and Classification Using Gram Matrix Embeddings on a Riemannian Manifold

X Zhang, Y Wang, M Gou, M Sznaier… - 2016 IEEE Conference …, 2016 - ieeexplore.ieee.org
In this paper we propose a new framework to compare and classify temporal sequences.
The proposed approach captures the underlying dynamics of the data while avoiding …
[PDF] archive.org

[PDF][PDF] Efficient Temporal Sequence Comparison and Classification using Gram Matrix Embeddings On a Riemannian Manifold

X Zhang, Y Wang, M Gou, M Sznaier, O Camps - scholar.archive.org
In this paper we propose a new framework to compare and classify temporal sequences.
The proposed approach captures the underlying dynamics of the data while avoiding …
[PDF] neu.edu

[PDF][PDF] Efficient Temporal Sequence Comparison and Classification using Gram Matrix Embeddings On a Riemannian Manifold

X Zhang, Y Wang, M Gou, M Sznaier, O Camps - robustsystems.coe.neu.edu
In this paper we propose a new framework to compare and classify temporal sequences.
The proposed approach captures the underlying dynamics of the data while avoiding …
[PDF] cv-foundation.org

[PDF][PDF] Efficient Temporal Sequence Comparison and Classification using Gram Matrix Embeddings On a Riemannian Manifold

X Zhang, Y Wang, M Gou, M Sznaier, O Camps - cv-foundation.org
In this paper we propose a new framework to compare and classify temporal sequences.
The proposed approach captures the underlying dynamics of the data while avoiding …