Oct 25, 2022 � This paper develops a novel multimodal core tensor factorization (MCTF) method combined with a tensor low-rankness measure and a better nonconvex relaxation�...
Nov 1, 2023 � This paper develops a novel multimodal core tensor factorization (MCTF) method combined with a tensor low-rankness measure and a better�...
Low-rank tensor completion has been widely used in computer vision and machine learning. This paper develops a novel multimodal core tensor factorization�...
Low-rank tensor completion has been widely used in computer vision and machine learning. This paper develops a novel multimodal core tensor factorization�...
Low-rank tensor completion has been widely used in computer vision and machine learning. This paper develops a novel multimodal core tensor factorization (MCTF)�...
This paper proposes a novel approach to tensor completion, which recovers missing entries of data represented by tensors. The approach is based on the tensor�...
Multimodal Core Tensor Factorization and its Applications to Low-Rank Tensor Completion � Computer Science, Mathematics. IEEE Transactions on Multimedia � 2023.
Multimodal Core Tensor Factorization and Its Applications to Low-Rank Tensor Completion � HAIJIN ZENG et. al. (Go back to Expert Search). Related Experts. Rank�...
Abstract. Higher-order low-rank tensors naturally arise in many applications including hyperspectral data recovery, video inpainting, seismic data recon-.
Our method preserves the low-rank structure of a tensor by factorizing it into the product of two tensors of smaller sizes. In the optimization process, our�...
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