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Image Completion in Embedded Space Using Multistage Tensor Ring Decomposition [PDF]

Frontiers in Artificial Intelligence, 2021
Tensor Completion is an important problem in big data processing. Usually, data acquired from different aspects of a multimodal phenomenon or different sensors are incomplete due to different reasons such as noise, low sampling rate or human mistake.
Farnaz Sedighin, Farnaz Sedighin, Andrzej Cichocki, Andrzej Cichocki   +3 more
doaj   +2 more sources

Moving objects detection based on tensor ring low rank decomposition [PDF]

Scientific Reports
The advancement of high-quality camera technology has increased the demand for efficient video analysis methods. Current methods mostly rely on matrix-based approaches, which break data structures and lose some spatial information.
Ruixuan Chen, Xusheng Li, Chenda Chen, Shiyu Zhu, Qipeng Chen, Jianting Cao   +5 more
doaj   +2 more sources

Low rank based FAZ segmentation in OCTA images [PDF]

Scientific Reports
Optical Coherence Tomography Angiography (OCTA) is a non-invasive method for vascular imaging of different tissues. Several diseases can disturb the blood supplying of retinal tissues which leads to loss of blood vessels and a reduction in the vascular ...
Farnaz Sedighin, Fatemeh Rezaei, Maryam Monemian   +2 more
doaj   +2 more sources

V3DQutrit a volumetric medical image segmentation based on 3D qutrit optimized modified tensor ring model [PDF]

Scientific Reports
This paper introduces 3D-QTRNet, a novel quantum-inspired neural network for volumetric medical image segmentation. Unlike conventional CNNs, which suffer from slow convergence and high complexity, and QINNs, which are limited to grayscale segmentation ...
Pratishtha Verma, Harish Kumar, Dhirendra Kumar Shukla, Sambit Satpathy, Deema Mohammed Alsekait, Osamah Ibrahim Khalaf, Ala Alzoubi, Basma S. Alqadi, Diaa Salama AbdElminaam, Arvinda Kushwaha, Jagriti Singh   +10 more
doaj   +2 more sources

A Novel Tensor Ring Sparsity Measurement for Image Completion [PDF]

Entropy
As a promising data analysis technique, sparse modeling has gained widespread traction in the field of image processing, particularly for image recovery.
Junhua Zeng, Yuning Qiu, Yumeng Ma, Andong Wang, Qibin Zhao   +4 more
doaj   +2 more sources

Tensor Ring Based Image Enhancement [PDF]

Journal of Medical Signals and Sensors
Background: Image enhancement, including image de-noising, super-resolution, registration, reconstruction, in-painting, and so on, is an important issue in different research areas.
Farnaz Sedighin
doaj   +2 more sources

Hyperspectral Image Super-Resolution Algorithm Based on Graph Regular Tensor Ring Decomposition

Remote Sensing, 2023
This paper introduces a novel hyperspectral image super-resolution algorithm based on graph-regularized tensor ring decomposition aimed at resolving the challenges of hyperspectral image super-resolution.
Shasha Sun, Wenxing Bao, Kewen Qu, Wei Feng, Xiaowu Zhang, Xuan Ma   +5 more
doaj   +1 more source

Application of Tensor Decomposition to Reduce the Complexity of Neural Min-Sum Channel Decoding Algorithm

Applied Sciences, 2023
Channel neural decoding is very promising as it outperforms the traditional channel decoding algorithms. Unfortunately, it still faces the disadvantage of high computational complexity and storage complexity compared with the traditional decoding ...
Qingle Wu, Benjamin K. Ng, Yuanhui Liang, Chan-Tong Lam, Yan Ma   +4 more
doaj   +1 more source

Weighted Group Sparse Regularized Tensor Decomposition for Hyperspectral Image Denoising

Applied Sciences, 2023
Hyperspectral imaging (HSI) has been used in a wide range of applications in recent years. But in the process of image acquisition, hyperspectral images are subject to various types of noise interference. Noise reduction algorithms can be used to enhance
Shuo Wang, Zhibin Zhu, Yufeng Liu, Benxin Zhang   +3 more
doaj   +1 more source

Hyperspectral-Multispectral Image Fusion via Tensor Ring and Subspace Decompositions

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Fusion from a spatially low resolution hyperspectral image (LR-HSI) and a spectrally low resolution multispectral image (MSI) to produce a high spatial-spectral HSI (HR-HSI), known as hyperspectral super resolution, has risen to a preferred topic for ...
Honghui Xu, Mengjie Qin, Sheng yong Chen, Yuhui Zheng, Jian wei Zheng   +4 more
doaj   +1 more source