Search Results - tensor convolutional sparse coding~

Deep High-Order Tensor Convolutional Sparse Coding for Hyperspectral Image Classification by Cheng, Chunbo, Li, Hong, Peng, Jiangtao, Cui, Wenjing, Zhang, Liming

“… In this article, a deep high-order tensor convolutional sparse coding (CSC) model is proposed, which can be used to train deep high-order filters…”
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Low-Rank Tensor Patching Based on Convolutional Sparse Coding for Communication Data Repair by Hu, Yi, Yao, Yuyi, Cheng, Zhen

“…). Based on the low-rank nature of the tensor, adding convolutional sparse coding (CSC) can well represent the characteristics of the high-frequency part of the information to handle the details while recovering the global information…”
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Tensor completion via convolutional sparse coding with small samples-based training by Liao, Tianchi, Wu, Zhebin, Chen, Chuan, Zheng, Zibin, Zhang, Xiongjun

“…•Our model outperforms state-of-the-art methods on three datasets of different types. Tensor data often suffer from missing value problems due to the complex high-dimensional structure while acquiring…”
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Two Layer Tensor Form Convolutional Sparse Coding for Stereo Matching by Cheng, Chunbo, Cui, Wenjing

“… Therefore, it is very important to establish a deep tensor model. In this paper, we propose a two layer tensor form convolutional sparse coding model, which can automatically learn the deep convolutional kernel…”
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Low Rank Activations for Tensor-Based Convolutional Sparse Coding by Humbert, Pierre, Audiffren, Julien, Oudre, Laurent, Vayatis, Nicolas

“…In this article, we propose to extend the classical Convolutional Sparse Coding model (CSC…”
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High Order Tensor Formulation for Convolutional Sparse Coding by Bibi, Adel, Ghanem, Bernard

“…Convolutional sparse coding (CSC) has gained attention for its successful role as a reconstruction and a classification tool in the computer vision and machine learning community…”
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RETRACTION: Low‐Rank Tensor Patching Based on Convolutional Sparse Coding for Communication Data Repair

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Online Tensor Robust Principal Component Analysis by Salut, Mohammad M., Anderson, David V.

“… Our algorithm is based on the recently proposed tensor singular value decomposition (T-SVD). We develop a convex optimization-based approach to recover the sparse component…”
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Deep High-order Tensor Convolutional Sparse Coding for Stereo Matching by Cui, Wenjing, Cheng, Chunbo

“… Therefore, it is very important to establish a deep high order tensor model. In this paper, we propose a deep high-order tensor convolutional sparse coding model, which can automatically learn the deep convolutional kernel…”
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Tensor Convolutional Sparse Coding with Low-Rank activations, an application to EEG analysis by Humbert, Pierre, Oudre, Laurent, Vayatis, Nivolas, Audiffren, Julien

“… However this encoding entails significant difficulties, especially for convolutional sparse coding (CSC…”
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Tensor Completion via Convolutional Sparse Coding Regularization by Wu, Zhebin, Liao, Tianchi, Chen, Chuan, Liu, Cong, Zheng, Zibin, Zhang, Xiongjun

“…) nor the Tensor Nuclear Norm (TNN) based methods. On the contrary, in the field of signal processing, Convolutional Sparse Coding (CSC…”
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Multivariate Convolutional Sparse Coding with Low Rank Tensor by Humbert, Pierre, Audiffren, Julien, Oudre, Laurent, Vayatis, Nicolas

“…This paper introduces a new multivariate convolutional sparse coding based on tensor algebra with a general model enforcing both element-wise sparsity and low-rankness of the activations tensors…”
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MF-LRTC: Multi-filters guided low-rank tensor coding for image restoration by Lu, Hongyang, Li, Sanqian, Liu, Qiegen, Zhang, Minghui

“…•The MF-LRTC takes advantages of the low-rank tensor coding to capture the sparse convolutional features generated by multi-filters representation…”
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Sparsity-Enhanced Convolutional Decomposition: A Novel Tensor-Based Paradigm for Blind Hyperspectral Unmixing by Yao, Jing, Hong, Danfeng, Xu, Lin, Meng, Deyu, Chanussot, Jocelyn, Xu, Zongben

“… the complex HSI still remains limited. To this end, this article presents a novel blind HU model, called sparsity-enhanced convolutional decomposition (SeCoDe…”
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Tensor Convolutional Dictionary Learning With CP Low-Rank Activations by Humbert, Pierre, Oudre, Laurent, Vayatis, Nicolas, Audiffren, Julien

“…In this paper, we propose to extend the standard Convolutional Dictionary Learning problem to a tensor representation where the activations are constrained to be "low-rank" through a Canonical Polyadic decomposition…”
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Deep Content-Dependent 3-D Convolutional Sparse Coding for Hyperspectral Image Denoising by Yin, Haitao, Chen, Hao

“… To tackle these issues, we first propose a content-dependent 3-D convolutional sparse coding (CD-CSC…”
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Deep Convolutional Neural Network Compression via Coupled Tensor Decomposition by Sun, Weize, Chen, Shaowu, Huang, Lei, So, Hing Cheung, Xie, Min

“… Recently, matrix and tensor decompositions have been employed for compressing neural networks…”
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Factorized Tensor Dictionary Learning for Visual Tensor Data Completion by Xu, Ruotao, Xu, Yong, Quan, Yuhui

“…; however, the expressibility of the resulting dictionary is rather limited. To address such issues, we propose a convolutional analysis model for tensor dictionary…”
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MF-LRTC: Multi-filters guided low-rank tensor coding for image restoration by Lu, Hongyang, Li, Sanqian, Liu, Qiegen, Wang, Yuhao

“… The MF-LRTC takes advantages of the low-rank tensor coding to capture the sparse convolutional features generated by multi-filters representation…”
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Learning Separable Filters by Sironi, Amos, Tekin, Bugra, Rigamonti, Roberto, Lepetit, Vincent, Fua, Pascal

“…Learning filters to produce sparse image representations in terms of over-complete dictionaries has emerged as a powerful way to create image features for many different purposes…”
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