Results 31 to 40 of about 6,366,089 (278)

Nonlinear Manifold Learning Integrated with Fully Convolutional Networks for PolSAR Image Classification

Remote Sensing, 2020
Synthetic Aperture Rradar (SAR) provides rich ground information for remote sensing survey and can be used all time and in all weather conditions. Polarimetric SAR (PolSAR) can further reveal surface scattering difference and improve radar’s ...
Chu He, Mingxia Tu, Dehui Xiong, Mingsheng Liao   +3 more
doaj   +1 more source

Rolling Element Bearing Fault Diagnosis Using Improved Manifold Learning

IEEE Access, 2017
Fault feature can be extracted by traditional manifold learning algorithms, which construct neighborhood graphs by Euclidean distance (ED). It is difficult to get an excellent dimensionality reduction result when processed data has strong correlations ...
Beibei Yao, Peng Zhen, Lifeng Wu, Yong Guan   +3 more
doaj   +1 more source

An Effective Manifold Learning Approach to Parametrize Data for Generative Modeling of Biosignals

IEEE Access, 2020
Modeling data generated by physiological systems is a crucial step in many problems such as classification, signal reconstruction and data augmentation.
Lorenzo Manoni, Claudio Turchetti, Laura Falaschetti   +2 more
doaj   +1 more source

LKLR: A Local Tangent Space-Alignment Kernel Least-Squares Regression Algorithm

Tsinghua Science and Technology, 2019
In the fields of machine learning and data mining, label learning is a nascent area of research, and within this paradigm, there is much room for improving multi-label manifold learning algorithms for high-dimensional data.
Chao Tan, Genlin Ji
doaj   +1 more source

Prototype Regularized Manifold Regularization Technique for Semi-Supervised Online Extreme Learning Machine

Sensors, 2022
Data streaming applications such as the Internet of Things (IoT) require processing or predicting from sequential data from various sensors. However, most of the data are unlabeled, making applying fully supervised learning algorithms impossible.
Muhammad Zafran Muhammad Zaly Shah, Anazida Zainal, Fuad A. Ghaleb, Abdulrahman Al-Qarafi, Faisal Saeed   +4 more
doaj   +1 more source

Manifold Learning and Nonlinear Homogenization

Multiscale Modeling & Simulation, 2022
We describe an efficient domain decomposition-based framework for nonlinear multiscale PDE problems. The framework is inspired by manifold learning techniques and exploits the tangent spaces spanned by the nearest neighbors to compress local solution manifolds.
Shi Chen 0003, Qin Li 0007, Jianfeng Lu 0001, Stephen J. Wright 0001   +3 more
openaire   +2 more sources

Perturbing low dimensional activity manifolds in spiking neuronal networks.

PLoS Computational Biology, 2019
Several recent studies have shown that neural activity in vivo tends to be constrained to a low-dimensional manifold. Such activity does not arise in simulated neural networks with homogeneous connectivity and it has been suggested that it is indicative ...
Emil Wärnberg, Arvind Kumar
doaj   +1 more source

Multilabel Learning with Incomplete Using Dual-Manifold Mapping [PDF]

Jisuanji gongcheng
In multilabel learning, the classification performance can be improved through the effective use of label correlations. However, owing to the subjectivity of manual tagging and the similarity of label semantics in practical applications, an incomplete ...
XU Zhilei, HUANG Rui
doaj   +1 more source

B-Manifold/pytorch_fnet_UwUnet: v1.0.0

, 2020
Release for citable code.
B-Manifold
core   +1 more source

Adaptive Safe Semi-Supervised Extreme Machine Learning

IEEE Access, 2019
Semi-supervised learning (SSL) based on manifold regularization (MR) is an excellent learning framework. However, the performance of SSL heavily depends on the construction of manifold graph and the safety degrees of unlabeled samples.
Jun Ma, Chao Yuan
doaj   +1 more source