Results 51 to 60 of about 3,449 (252)

Hyperspectral Image Denoising via Low-Rank Tucker Decomposition with Subspace Implicit Neural Representation

Remote Sensing
Hyperspectral image (HSI) denoising is an important preprocessing step for downstream applications. Fully characterizing the spatial-spectral priors of HSI is crucial for denoising tasks.
Cheng Cheng, Dezhi Sun, Yaoyuan Yang, Zhoucheng Guo, Jiangjun Peng   +4 more
doaj   +1 more source

Point Cloud Denoising Based on Tensor Tucker Decomposition [PDF]

2019 IEEE International Conference on Image Processing (ICIP), 2019
5 pages, 1 ...
Jianze Li, Xiao-Ping (Steven) Zhang, Tuan Tran   +2 more
openaire   +2 more sources

Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion

Advanced Robotics Research, EarlyView.
A compliant pneumatic foot with real‐time variable stiffness enables humanoid robots to adapt to changing terrains. Using onboard vision and pressure control, the foot modulates stiffness within each gait cycle, reducing impact forces and improving balance. The design, cast in soft silicone with embedded air chambers and Kevlar wrapping, offers durable,
Irene Frizza, Hiroshi Kaminaga, Philippe Fraisse, Gentiane Venture   +3 more
wiley   +1 more source

A tensor compression algorithm using Tucker decomposition and dictionary dimensionality reduction

International Journal of Distributed Sensor Networks, 2020
Tensor compression algorithms play an important role in the processing of multidimensional signals. In previous work, tensor data structures are usually destroyed by vectorization operations, resulting in information loss and new noise. To this end, this
Chenquan Gan, Junwei Mao, Zufan Zhang, Qingyi Zhu   +3 more
doaj   +1 more source

Single‐Cell Dissection of Therapy‐Induced Remodeling Uncovers a Fibroblast‐Driven Immunosuppressive Niche and Targetable Vulnerabilities in Lethal Prostate Cancer

Advanced Science, EarlyView.
Single‐cell longitudinal profiling reveals that androgen‐deprivation therapy induces a DPT+ fibroblast‐complement axis that suppresses macrophage inflammation and drives CD8+ T cell exhaustion in prostate cancer. Concurrently, resistant epithelial subpopulations persist and engage TSPAN1‐ and NRXN1‐mediated programs promoting CRPC and neuroendocrine ...
Yang Chen, Dandan Dong, Jinling Liao, Naikai Liao, Mengqi Liu, Qin Zhang, Siting Chen, Qi Liu, Ying Lu, Tianyu Li, Chunlin Zou, Qiong Song, Qiuyan Wang, Jian Liang, Qiji Xie, Chengyang Li, Mengyun Wang, Jiwen Cheng, Zengnan Mo, Gong‐Hong Wei   +19 more
wiley   +1 more source

Hypergraph regularized nonnegative triple decomposition for multiway data analysis

Scientific Reports
Tucker decomposition is widely used for image representation, data reconstruction, and machine learning tasks, but the calculation cost for updating the Tucker core is high.
Qingshui Liao, Qilong Liu, Fatimah Abdul Razak   +2 more
doaj   +1 more source

Tucker Decomposition Network: Expressive Power and Comparison

CoRR, 2019
Deep neural networks have achieved a great success in solving many machine learning and computer vision problems. The main contribution of this paper is to develop a deep network based on Tucker tensor decomposition, and analyze its expressive power. It is shown that the expressiveness of Tucker network is more powerful than that of shallow network. In
Ye Liu 0014, JunJun Pan, Michael K. Ng 0001   +2 more
openaire   +2 more sources

Integrative Multi‐Omics Analysis Reveals a Mitochondrial–Immune Axis Associated With Neoadjuvant Chemotherapy Response in High‐Grade Serous Ovarian Cancer

Advanced Science, EarlyView.
Integrative multi‐omics analysis delineates a mitochondrial–immune axis governing neoadjuvant chemotherapy response in high‐grade serous ovarian cancer. Immune‐active tumors exhibit enhanced B‐cell infiltration and favorable sensitivity, whereas metabolically rewired tumors display oxidative phosphorylation dependency and resistance.
Wei Jiang, Yi Wang, Xiaohang Lu, Qianlan Yao, Libing Xiang, Xu Cai, Xiaoyu Tu, Shaoxian Tang, Ying Xu, Yufan Cheng, Liming Shen, Huijuan Yang   +11 more
wiley   +1 more source

Tucker Decomposition-Based Network Compression for Anomaly Detection With Large-Scale Hyperspectral Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Deep learning methodologies have demonstrated considerable effectiveness in hyperspectral anomaly detection (HAD). However, the practicality of deep learning-based HAD in real-world applications is impeded by challenges arising from limited labeled data,
Yulei Wang, Hongzhou Wang, Enyu Zhao, Meiping Song, Chunhui Zhao   +4 more
doaj   +1 more source

Faster Quantum State Decomposition with Tucker Tensor Approximation

Quantum Machine Intelligence, 2022
Abstract Researchers have put a lot of effort into reducing the gap between current quantum processing units (QPU) capabilities and their potential supremacy.One approach is to keep supplementary computations in the CPU, and use QPU only for the core of the problem.
Protasov Stanislav, Lisnichenko Marina
openaire   +1 more source