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Found 16 papers, 1 papers with code
A Theoretically Guaranteed Quaternion Weighted Schatten p-norm Minimization Method for Color Image Restoration
Very recently, a quaternion-based WNNM approach (QWNNM) has been developed to mitigate this issue, which is capable of representing the color image as a whole in the quaternion domain and preserving the inherent correlation among the three color channels.
SOC: hunting the underground inside story of the ethereum Social-network Opinion and Comment
Ethereum is gaining a significant popularity in blockchain community, mainly due to the fact that it is designed in a way that enables developers to write smart contracts and decentralized applications (Dapps).
Fine-Grained Car Detection for Visual Census Estimation
In this work, we leverage the ubiquity of Google Street View images and develop a computer vision pipeline to predict income, per capita carbon emission, crime rates and other city attributes from a single source of publicly available visual data.
Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the US
The United States spends more than $1B each year on initiatives such as the American Community Survey (ACS), a labor-intensive door-to-door study that measures statistics relating to race, gender, education, occupation, unemployment, and other demographic factors.
Support Driven Wavelet Frame-based Image Deblurring
The wavelet frame systems have been playing an active role in image restoration and many other image processing fields over the past decades, owing to the good capability of sparsely approximating piece-wise smooth functions such as images.
A method of the transfer graphene based on sublimed method 2015 CN ZL201510962569.0
The invention discloses a kind of methods of transfer graphene. This method is using the substance easily to distil as the supporting layer of transfer graphene, first by heating easy sublimate, its graphene surface on being grown on initial substrate is set to sublimate to form fine and close supporting layer, then it removes initial substrate and graphene/supporting layer is transferred to target substrate, then supporting layer is distilled. Compared to residue glue problem existing for existing PMMA methods, PDMS methods and hot stamping, heat release tape method to target substrate planarization, adhesion requirement is higher the problems such as, the present invention uses easy sublimate as supporting layer, transfer process is simpler, convenient, can be achieved large area from graphene to arbitrary target substrate, it is lossless, shifted without residue glue, graphene will be expanded significantly in terms of flexible electronic, organic nano electronics, organic solar batteries, organic sensor, the application in the fields such as organic High-performance micro-nano electronic device, organic material energy stores.
Wavelet Frame Based Image Restoration Using Sparsity, Nonlocal and Support Prior of Frame Coefficients
Very recently, the authors in \cite{Chen2015} proposed $l_0$-$l_2$ minimization model, where the nonlocal prior of frame coefficients is incorporated.
A Novel Approach for Stable Selection of Informative Redundant Features from High Dimensional fMRI Data
Feature selection is among the most important components because it not only helps enhance the classification accuracy, but also or even more important provides potential biomarker discovery.
Randomized Structural Sparsity based Support Identification with Applications to Locating Activated or Discriminative Brain Areas: A Multi-center Reproducibility Study
In this paper, we focus on how to locate the relevant or discriminative brain regions related with external stimulus or certain mental decease, which is also called support identification, based on the neuroimaging data.
Linear Spatial Pyramid Matching Using Non-convex and non-negative Sparse Coding for Image Classification
Recently sparse coding have been highly successful in image classification mainly due to its capability of incorporating the sparsity of image representation.
Sensitivity Analysis for Computationally Expensive Models using Optimization and Objective-oriented Surrogate Approximations
In addition, the performance of Kriging is not as good as Gaussian RBF, especially in the case of high dimensional problems.
A General Stochastic Algorithmic Framework for Minimizing Expensive Black Box Objective Functions Based on Surrogate Models and Sensitivity Analysis
We are focusing on bound constrained global optimization problems, whose objective functions are computationally expensive black-box functions and have multiple local minima.
Randomized Structural Sparsity via Constrained Block Subsampling for Improved Sensitivity of Discriminative Voxel Identification
In this paper, we consider voxel selection for functional Magnetic Resonance Imaging (fMRI) brain data with the aim of finding a more complete set of probably correlated discriminative voxels, thus improving interpretation of the discovered potential biomarkers.
Multi-stage Multi-task feature learning via adaptive threshold
However, this algorithm harnesses a prescribed fixed threshold in the definition of the capped-$\ell_{1},\ell_{1}$ regularization and the lack of adaptivity might result in suboptimal performance.
Truncated Nuclear Norm Minimization for Image Restoration Based On Iterative Support Detection
Recovering a large matrix from limited measurements is a challenging task arising in many real applications, such as image inpainting, compressive sensing and medical imaging, and this kind of problems are mostly formulated as low-rank matrix approximation problems.
FTVd is beyond Fast Total Variation regularized Deconvolution
In this paper, we revisit the "FTVd" algorithm for Fast Total Variation Regularized Deconvolution, which has been widely used in the past few years.
