Suchergebnisse - tensor sparse coding

Enhancing Low‐Light Images: A Variation‐based Retinex with Modified Bilateral Total Variation and Tensor Sparse Coding von Yang, Weipeng, Gao, Hongxia, Zou, Wenbin, Huang, Shasha, Chen, Hongsheng, Ma, Jianliang

“… Additionally, tensor sparse coding is employed as a regularization term to remove noise and artifacts from the reflectance component …”
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Tensor Sparse Coding for Positive Definite Matrices von Sivalingam, Ravishankar, Boley, Daniel, Morellas, Vassilios, Papanikolopoulos, Nikolaos

“… This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without …”
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Kernel Tensor Sparse Coding Model for Precise Crop Classification of UAV Hyperspectral Image von Yang, Lixia, Zhang, Rui, Bao, Yajun, Yang, Shuyuan, Jiao, Licheng

“… In this letter, a kernel tensor sparse coding model (KTSCM) is proposed for precise crop classification of unmanned aerial vehicle (UAV …”
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Deep High-Order Tensor Convolutional Sparse Coding for Hyperspectral Image Classification von 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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Superpixel Tensor Sparse Coding for Structural Hyperspectral Image Classification von Feng, Zhixi, Wang, Min, Yang, Shuyuan, Liu, Zhi, Liu, Linzan, Wu, Bin, Li, Hong

“… In this paper, a superpixel tensor sparse coding (STSC) based hyperspectral image classification (HIC …”
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Time–frequency audio feature extraction based on tensor representation of sparse coding von Zhang, Xue-Yuan, He, Qian-Hua

“… The tensor, derived from a weight vector and a Gabor dictionary in sparse coding, represents the frequency, time centre and scale of transient time …”
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Precise crop classification of UAV hyperspectral imagery using kernel tensor slice sparse coding based classifier von Yang, Lixia, Chen, Jinwei, Zhang, Rui, Yang, Shuyuan, Zhang, Xinyu, Jiao, Licheng

“… •The KTSSOMP algorithm adaptively learns the sparse coding coefficients of KTSSCC.•There are very few parameters in our proposed KTSSCC model …”
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Nonlocal Patch Tensor Sparse Representation for Hyperspectral Image Super-Resolution von Yang Xu, Zebin Wu, Chanussot, Jocelyn, Zhihui Wei

“… learning, and tensor sparse coding together. Finally, alternating direction …”
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3-D Seismic Noise Attenuation via Tensor Sparse Coding With Spatially Adaptive Coherence Constraint von He, Xin, Qian, Feng, Fan, Yuqi, Feng, Lingtian, Hu, Guangmin

“… Tensor sparse coding (TSC) is a method used to excavate 3D volume structures extended by sparse coding (SC …”
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Hyperspectral Image Classification via Slice Sparse Coding Tensor based Classifier with Compressive Dimensionality Reduction von Yang, Lixia, Zhang, Rui, Yang, Shuyuan, Jiao, Licheng

“… The obtained sparse coding coefficients could be regarded as a Slice Sparse Coding Tensor (SSCT), which can be adaptively learnt and utilized to predict the labels of HSI pixels …”
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Tensor LRR and Sparse Coding-Based Subspace Clustering von Yifan Fu, Junbin Gao, Tien, David, Zhouchen Lin, Xia Hong

“… To address these issues, we propose a tensor low-rank representation (TLRR) and sparse coding-based (TLRRSC …”
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Low-Rank Tensor Patching Based on Convolutional Sparse Coding for Communication Data Repair von 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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K-CPD: Learning of overcomplete dictionaries for tensor sparse coding von Guifang Duan, Hongcui Wang, Zhenyu Liu, Junping Deng, Yen-Wei Chen

“… In this paper, we propose a new algorithm of overcomplete dictionary learning for tensor sparse coding, named K-CPD, by extension of K-SVD [8 …”
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A Novel Two-Dimensional Tensor Sparse Coding Algorithm for Image Representation von Lu, Jiaren, Jiang, Fei, Shen, Ruimin

“… In this paper, we propose a novel two-dimensional sparse coding (2DSC) model that represents gray images as the tensor-linear combinations under a novel algebraic framework …”
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Semi-Tensor Sparse Vector Coding for Short-Packet URLLC with Low Storage Overhead von Zhang, Yanfeng, Fan, Xian, Liang, Hui, Yang, Weiwei, Zheng, Jinkai, Luan, Tom H.

“… Sparse vector coding (SVC) is a promising short-packet transmission method for ultra reliable low latency communication (URLLC …”
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Learning-Based Lossless Point Cloud Geometry Coding Using Sparse Tensors von Nguyen, Dat Thanh, Kaup, Andre

“… Specifically, our method uses a sparse convolution neural network to estimate the voxel occupancy sequentially from the x, y, z input data …”
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Laplacian Tensor sparse coding for image categorization von Dammak, Mouna, Mejdoub, Mahmoud, Ben Amar, Chokri

“… Yet, this method neglects the relationships among features. To reduce the impact of this issue, we suggest in this paper, a Laplacian Tensor sparse coding method, which will aim to profit from the relationship among the local features …”
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Tensor completion via convolutional sparse coding with small samples-based training von 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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Hybrid Probabilistic Sparse Coding With Spatial Neighbor Tensor for Hyperspectral Imagery Classification von Yang, Lixia, Wang, Min, Yang, Shuyuan, Zhao, Hui, Jiao, Licheng, Feng, Xiangchu

“… Under the umbrella of tensor algebra, this paper proposes a new sparse-coding-based classifier (SCC …”
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Tensor Sparse Coding for Positive Definite Matrices von Sivalingam, Ravishankar, Boley, Daniel, Morellas, Vassilios, Papanikolopoulos, Nikos

“… This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without …”
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