Results 11 to 20 of about 223,331 (198)
Semantic sensitive tensor factorization
Artificial Intelligence, 2016 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Makoto Nakatsuji +4 more
openaire +4 more sources
Gregarious Kite Factorization of Tensor Product of Complete Graphs [PDF]
Discussiones Mathematicae Graph Theory, 2020 A kite factorization of a multipartite graph is said to be gregarious if every kite in the factorization has all its vertices in different partite sets. In this paper, we show that there exists a gregarious kite factorization of Km × Kn if and only if mn
Tamil Elakkiya A., Muthusamy A.
doaj +2 more sources
A New Model for Tensor Completion: Smooth Convolutional Tensor Factorization
IEEE Access, 2023 Tensor completion is the problem of filling-in missing parts of multidimensional data using the values of the reference elements. Recently, Multiway Delay-embedding Transform (MDT), which considers a low-dimensional space in a delay-embedded space with ...
Hiromu Takayama, Tatsuya Yokota
doaj +3 more sources
Generalized Discriminant Orthogonal Nonnegative Tensor Factorization for Facial Expression Recognition [PDF]
The Scientific World Journal, 2014 In order to overcome the limitation of traditional nonnegative factorization algorithms, the paper presents a generalized discriminant orthogonal non-negative tensor factorization algorithm.
Zhang XiuJun, Liu Chang
doaj +2 more sources
Tensor factorization toward precision medicine. [PDF]
Brief Bioinform, 2017 Precision medicine initiatives come amid the rapid growth in quantity and variety of biomedical data, which exceeds the capacity of matrix-oriented data representations and many current analysis algorithms. Tensor factorizations extend the matrix view to
Luo Y, Wang F, Szolovits P.
europepmc +2 more sources
Sparse and Low-Rank Constrained Tensor Factorization for Hyperspectral Image Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Third-order tensors have been widely used in hyperspectral remote sensing because of their ability to maintain the 3-D structure of hyperspectral images.
Pan Zheng, Hongjun Su, Qian Du
doaj +1 more source
Frontiers in Earth Science, 2023 Restoration of hyperspectral images (HSI) is a crucial step in many potential applications as a preprocessing step. Recently, low-rank tensor ring factorization was applied for HSI reconstruction, which has high-order tensors’ powerful and generalized ...
Xuegang Luo +5 more
doaj +1 more source
Tensor factorization via transformed tensor-tensor product for image alignment
Numerical Algorithms, 2023 In this paper, we study the problem of a batch of linearly correlated image alignment, where the observed images are deformed by some unknown domain transformations, and corrupted by additive Gaussian noise and sparse noise simultaneously. By stacking these images as the frontal slices of a third-order tensor, we propose to utilize the tensor ...
Sijia Xia, Duo Qiu, Xiongjun Zhang
openaire +4 more sources
Hyperspectral and Multispectral Image Fusion Using Coupled Non-Negative Tucker Tensor Decomposition
Remote Sensing, 2021 Fusing a low spatial resolution hyperspectral image (HSI) with a high spatial resolution multispectral image (MSI), aiming to produce a super-resolution hyperspectral image, has recently attracted increasing research interest.
Marzieh Zare +3 more
doaj +1 more source
Alzheimer’s Disease Recognition Applying Non-Negative Matrix Factorization Characteristics from Brain Magnetic Resonance Images (MRI) [PDF]
E3S Web of Conferences, 2023 To more accurately depict Alzheimer’s disease (AD) and projecting clinical outcomes while taking into account advancements in clinical imaging and substantial learning, several experts are gradually using ConvNet (CNNs) to remove deep intensity features ...
Reddy G. Vijendar +4 more
doaj +1 more source