Seismic vulnerability of above-ground storage tanks with unanchored support conditions for Na-tech risks based on Gaussian process regression
Sign Up to like & getrecommendations! Published in 2020 at "Bulletin of Earthquake Engineering"
DOI: 10.1007/s10518-020-00960-7
Abstract: This paper aims to investigate the seismic vulnerability of an existing unanchored steel storage tank ideally installed in a refinery in Sicily (Italy), along the lines of performance-based earthquake engineering. Tank performance is estimated by… read more here.
Keywords: storage; process regression; based gaussian; vulnerability ... See more keywords
A novel approach for solid particle erosion prediction based on Gaussian Process Regression
Sign Up to like & getrecommendations! Published in 2021 at "Wear"
DOI: 10.1016/j.wear.2020.203549
Abstract: Abstract Based on Gaussian Process Regression (GPR) method, a novel non-linear approach is adopted to predict solid particle erosion in standard elbows. Several data sets extracted from Computational Fluid Dynamics (CFD) results and experimental tests… read more here.
Keywords: particle erosion; erosion; solid particle; based gaussian ... See more keywords
An Efficient Gaussian Filter Based on Gaussian Symmetric Markov Random Field
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3191335
Abstract: This article presents a new image denoising algorithm that uses Gaussian Symmetric Markov random fields based on maximum a posteriori estimation. First, an image denoising model based on Gaussian Symmetric Markov random fields is built,… read more here.
Keywords: random field; symmetric markov; markov random; gaussian symmetric ... See more keywords
Trajectory plan for an ultra-short distance on-orbit service based on the Gaussian pseudo-spectral method
Sign Up to like & getrecommendations! Published in 2018 at "IEEE/CAA Journal of Automatica Sinica"
DOI: 10.1109/jas.2017.7510892
Abstract: Considering the ultra-short distance approaching plan of on-orbit service, the trajectory plan strategy based on the Gaussian pseudo-spectral method is researched. Given the target spinning, safety, fuel and maneuver factors, a model which contains a… read more here.
Keywords: pseudo spectral; orbit service; trajectory; based gaussian ... See more keywords
A Compressive Tracking Method Based on Gaussian Differential Graph and Weighted Cosine Similarity Metric
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2016.2603170
Abstract: This letter presents an extended compressive tracking algorithm to increase the stabilization and robustness in scale variation, rotation, and illumination variation. The features are extracted from the Gaussian differential graphs and taken as input signals… read more here.
Keywords: compressive tracking; tracking method; method based; differential graph ... See more keywords
Transfer-Learning-Based Gaussian Mixture Model for Distributed Clustering.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2022.3177242
Abstract: Distributed clustering based on the Gaussian mixture model (GMM) has exhibited excellent clustering capabilities in peer-to-peer (P2P) networks. However, more iterative numbers and communication overhead are required to achieve the consensus in existing distributed GMM… read more here.
Keywords: transfer; distributed clustering; transfer learning; mixture model ... See more keywords
A Synthetic Minority Oversampling Technique Based on Gaussian Mixture Model Filtering for Imbalanced Data Classification.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3197156
Abstract: Data imbalance is a common phenomenon in machine learning. In the imbalanced data classification, minority samples are far less than majority samples, which makes it difficult for minority to be effectively learned by classifiers A… read more here.
Keywords: synthetic minority; minority; imbalanced data; oversampling technique ... See more keywords
Developing a Robust Model Based on the Gaussian Process Regression Approach to Predict Biodiesel Properties
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Chemical Engineering"
DOI: 10.1155/2021/5650499
Abstract: Biodiesel is assumed a renewable and environmentally friendly fuel that possesses the potential to substitute petroleum diesel. The basic purpose of the present study is to design a precise algorithm based on Gaussian Process Regression… read more here.
Keywords: process regression; biodiesel; based gaussian; biodiesel properties ... See more keywords
A novel pooling layer based on gaussian function with wavelet transform
Sign Up to like & getrecommendations! Published in 2020 at "Indonesian Journal of Electrical Engineering and Computer Science"
DOI: 10.11591/ijeecs.v20.i3.pp1289-1298
Abstract: Convolution represent basic layer in the convolutional neural network, but it can result in big size of the data, which may increase the complexity of the network. Different pooling methods are used to perform down… read more here.
Keywords: wavelet; function; based gaussian; method ... See more keywords
Automatic elimination of phase aberrations in digital holography based on Gaussian 1σ- criterion and histogram segmentation.
Sign Up to like & getrecommendations! Published in 2023 at "Optics express"
DOI: 10.1364/oe.486890
Abstract: We propose a numerical and automatic quadratic phase aberration elimination method in digital holography for phase-contrast imaging. A histogram segmentation method based on Gaussian 1σ-criterion is used to obtain the accurate coefficients of quadratic aberrations… read more here.
Keywords: digital holography; gaussian criterion; histogram segmentation; phase ... See more keywords
Probabilistic Attention based on Gaussian Processes for Deep Multiple Instance Learning
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on neural networks and learning systems"
DOI: 10.48550/arxiv.2302.04061
Abstract: Multiple instance learning (MIL) is a weakly supervised learning paradigm that is becoming increasingly popular because it requires less labeling effort than fully supervised methods. This is especially interesting for areas where the creation of… read more here.
Keywords: probabilistic attention; multiple instance; instance learning; instance ... See more keywords