Algorithm finds function contours using multiple approximations.
problem Locating contours of expensive-to-evaluate functions.
method Uses multiple biased and noisy approximations to locate contours efficiently by maximizing entropy reduction.
result Maximizes reduction of contour entropy per unit cost.
Defines surfaces with specific contour patterns.
problem Characterizing surfaces with concentric or parallel K-contours. method Presented examples and characterization given.
result Characterization of surfaces with concentric or parallel K-contours. FineFool attacks deep models by focusing on object contours, improving attack performance.
problem Adversarial attacks on deep learning models, especially those that focus on perturbation size and success rate.
method FineFool uses attention to focus on object contours, producing more efficient and imperceptible perturbations.
result FineFool achieves better attack performance compared to state-of-the-art attacks, including higher success rate and smaller perturbations.
Study bifurcation diagrams of crosscap contours.
problem Understanding bifurcations in crosscap images.
method Determined precise bifurcation diagrams of crosscap contours.
result Three types of equivalences are crucial for bifurcations.
A contour integral method recently proposed by Weideman [IMA J. Numer. Anal., to appear] for integrating semi-discrete advection-diffusion PDEs, is extended for application to some of the important equations of mathematical finance. Using estimates for the numerical range of the spatial operator, optimal contour parame…
Describing shapes by suitable measures in object segmentation, as proposed in [24], allows to combine the advantages of the representations as parametrized contours and indicator functions. The pseudo-Riemannian structure of optimal transport can be used to model shapes in ways similar as with contours, while the Kanto…
Investigate the local geometry of smooth surfaces in 4-space via contact with 2-planes and apparent contours.
problem Local geometry of smooth surfaces in 4-space
method Contact with 2-planes and apparent contour
result Prove connections between singularities of parallel projections, orthogonal projections, and height functions.
In this paper we consider planar sections and visual contours of co-dimension one affine immersions. The main theorem says that the third order Taylor expansion of the difference between the visual contour and planar section functions is exactly the cubic form. We also consider parameterizations on two dimensional affi…
Metrics stabilize persistent homology in data analysis.
problem Stabilizing invariants for characterizing connectivity structures in data.
method Using contour functions to define metrics for rank invariants.
result Optimal contours provide robust descriptors of spatial patterns.
Paper proposes a new Wasserstein distance for mixtures of radially contoured distributions.
problem Generalization of Wasserstein distance to non-elliptically contoured distributions.
method Relaxed formulation for mixtures of radially contoured distributions without marginal consistency.
result The new distance yields more stable error and better color distribution in image transfer tasks.
Improved F0 contour estimation from noisy speech with higher frequency resolution.
problem Estimating the fundamental frequency contour of speech from noisy audio.
method Regression model using recurrent deep neural networks trained on supervised learning.
result Improves F0 contour estimation by more than 25% at SNRs between -10 dB and +10 dB.
We develop mask iterative hard thresholding algorithms (mask IHT and mask DORE) for sparse image reconstruction of objects with known contour. The measurements follow a noisy underdetermined linear model common in the compressive sampling literature. Assuming that the contour of the object that we wish to reconstruct i…
Exploration of hydrocarbon resources is a highly complicated and expensive process where various geological, geochemical and geophysical factors are developed then combined together. It is highly significant how to design the seismic data acquisition survey and locate the exploratory wells since incorrect or imprecise …
A new method for analyzing shapes using FDA techniques.
problem Statistical shape analysis of deformed contours.
method Functional Data Analysis (FDA) with basis expansion and principal component analysis.
result Successfully identifies deformation parameters and captures contour distributions.
The paper studies curves in surfaces using flow-spines and apparent contours.
problem Understanding curves in arbitrary surfaces using flow-spines and apparent contours.
method By considering generic curves and their apparent contours relative to a traversing flow, the paper reconstructs curves and allows them to vary up to homotopy.
result A finite set of local moves on decorated graphs allows for the reconstruction and variation of curves within a fixed generic flow.
IrisNet tracks tongue contours in ultrasound videos using deep learning.
problem Automatic and real-time tracking of tongue contours in ultrasound videos.
method Convolutional neural network mimicking peripheral vision.
result Outstanding generalization on various ultrasound tongue datasets.
The contour map of estimation error of Expected Shortfall (ES) is constructed. It allows one to quantitatively determine the sample size (the length of the time series) required by the optimization under ES of large institutional portfolios for a given size of the portfolio, at a given confidence level and a given esti…
ICSGLD improves efficiency in posterior sampling for big data.
problem Efficient posterior sampling for large datasets.
method Embarrassingly parallel multiple-chain CSGLD with efficient interactions.
result ICSGLD is more efficient than a single-chain CSGLD.
We present a new implementation of anisotropic mean curvature flow for contour recognition. Our procedure couples the mean curvature flow of planar closed smooth curves, with an external field from a potential of point-wise charges. This coupling constrains the motion when the curve matches a picture placed as backgrou…
The paper finds surfaces closest to being flat that span a given contour.
problem Finding surfaces in R3 that are as flat as possible while spanning a given contour. method The approach involves minimizing the total Gaussian curvature squared and solving a system of PDEs.
result The optimal surface is shown to be controlled by a biharmonic equation with specific boundary conditions.
Completeness of the eigenfunctions of a quantum mechanical system is crucial for its probability interpretation. By using the method of contour integral we give properly normalized eigenfunctions for both discrete and continuum spectrum of the Morse potential, and explicitly prove the completeness relation. As an appli…
Proposes a new network to improve nuclei segmentation in histopathology images.
problem Challenges in separating overlapped nuclei in histopathology images.
method Introduces a bending loss regularized network to minimize contour points with large curvatures.
result Outperforms six state-of-the-art approaches on five quantitative metrics.
Improved image learning using elliptically contoured tensor-variate distributions.
problem Inadequate statistical analysis for tensor-valued data, especially with heavier or lighter tails.
method Developed a family of elliptically contoured tensor-variate distributions and derived their properties and procedures for estimation.
result Tensor-variate classification rules and tensor-on-tensor regression better predict and characterize data than TVN-based methods.
Filters in convolutional networks are typically parameterized in a pixel basis, that does not take prior knowledge about the visual world into account. We investigate the generalized notion of frames designed with image properties in mind, as alternatives to this parametrization. We show that frame-based ResNets and De…
In this paper we present a new method for motion tracking of tumors in liver ultrasound image sequences. Our algorithm has two main steps. In the first step, we apply mean shift algorithm with multiple features to estimate the center of the target in each frame. Target in the first frame is defined using an ellipse. Ed…
Optimizes learning Hilbert-Schmidt operators between Sobolev spaces.
problem Statistical limits of learning mappings between infinite-dimensional function spaces.
method Minimax optimal regularization and multilevel training.
result Multilevel kernel operator learning achieves optimal learning rate.
New methods improve accuracy in predicting complex systems.
problem Improving accuracy in predicting complex physical systems from simulators.
method Proposes two new methods of design approaches that sequentially select input settings.
result Demonstrates effectiveness of the proposed methods through numerical examples.
The contour maps of the error of historical resp. parametric estimates for large random portfolios optimized under the risk measure Expected Shortfall (ES) are constructed. Similar maps for the sensitivity of the portfolio weights to small changes in the returns as well as the VaR of the ES-optimized portfolio are also…
Study on Gaussian random fields' singularities on manifolds.
problem Understanding singularities of Gaussian random fields on manifolds.
method Computed expected values of singularities under various conditions.
result Explicit formulae for singularities under different constraints.
The paper tightens bounds on distances between Reeb graphs.
problem Certifying quasi-universality of distances between Reeb graphs.
method Establishes tight bi-Lipschitz bounds for various distances.
result Proves strict universality of the functional contortion distance for contour trees and coincides with interleaving distance for merge trees.
Study of curves and surfaces from single-direction projections.
problem Obtaining complete shape information from a single view.
method Theoretical study of differential geometric information from multiple orthogonal projections.
result Formulae for recovering certain information on curves or surfaces from their projections.
We present an approach for polarimetric Synthetic Aperture Radar (SAR) image region boundary detection based on the use of B-Spline active contours and a new model for polarimetric SAR data: the GHP distribution. In order to detect the boundary of a region, initial B-Spline curves are specified, either automatically or…
Study improves tongue contour recognition in ultrasound images using transfer learning.
problem Difficulty in recognizing tongue gestures due to low-contrast and noisy ultrasound images.
method Transfer learning with U-net and fine-tuning on different ultrasound datasets.
result Fine-tuned U-net models perform well on images from different ultrasound devices.
It is proposed a new code for contours of plane images. This code was applied for optical character recognition of printed and handwritten characters. One can apply it to recognition of any visual images.
Wilson loops in N=4 supersymmetric Yang-Mills theory correspond at strong coupling to extremal surfaces in AdS5. We study a class of extremal surfaces known as special Legendrian submanifolds. The "hemisphere" corresponding to the circular Wilson loop is an example of a special Legendrian submanifold, and w…
Combines geometric and topological info for complex object boundaries.
problem Boundary estimation for images with complex topologies.
method Topological clustering for initialization of Bayesian active contour model.
result Smart initialization reduces user dependence and improves accuracy.
We consider a complex Plateau problem for strongly pseudoconvex contours in non Kähler manifolds. A positive solution in the case of manifolds carrying a pluriclosed Hermitian metric forms is given. For the general case we propose a conjecture.
Wavelet features improve image clustering and segmentation accuracy.
problem Noise and lack of spatial context in pixel intensity-based methods.
method Modified K-means, Fuzzy c-means, and ACWE algorithms incorporating Wavelet features.
result Wavelet-based algorithms converge to different segmentation results based on frequency information.
New method improves combinatorial optimization by overcoming inefficient sampling.
problem Wandering in contours: sampling similar solutions for long periods.
method Reheated Gradient-based Discrete Sampling with a novel mechanism.
result Superior performance across various combinatorial optimization problems.
New formulas for surface curvature when tangent vector points in asymptotic directions.
problem Formula limitations when tangent vector points in asymptotic directions.
method Analogous formulas for surfaces with cusp singular points.
result Invariants of cusp singular points of contour lines.
A new algorithm flattens multi-modal distributions for better deep learning.
problem Bayesian learning in big data with multi-modal distributions.
method Contour Stochastic Gradient Langevin Dynamics (CSGLD) algorithm.
result The CSGLD algorithm avoids local traps in deep neural networks.
Entropy-based GP adaptive design improves failure probability estimation.
problem Limited accuracy in failure probability estimation due to model evaluation costs.
method Entropy-based Gaussian process (GP) adaptive design combined with multifidelity importance sampling (MFIS).
result More accurate failure probability estimates and higher confidence.
We explore a connection between the Finslerian area functional and well-investigated Cartan functionals to prove new Bernstein theorems, uniqueness and removability results for Finsler-minimal graphs, as well as enclosure theorems and isoperimetric inequalities for minimal immersions in Finsler spaces. In addition, we …
The paper reinterprets a quantum invariant using state integrals and contour integrals.
problem Quantum invariants of knots and their asymptotic behavior.
method Expressing the invariant as a sum over contour integrals in hyperbolic structures.
result Establishes a new integral representation for quantum invariants.
PFs and iPFs learn principal manifolds for efficient density estimation.
problem Understanding the geometric structure of normalizing flows.
method Characterize flows using principal manifolds and contours.
result PFs and iPFs can learn principal manifolds and perform density estimation.
This research bounds the complexity of Reeb graphs and their cycles, improving approximation of metric spaces.
problem Approximating the complexity of metric spaces using Reeb graphs.
method Analyzing the cycle rank of Reeb graphs and relating it to the co-rank of the fundamental group.
result The cycle rank of a Reeb graph is bounded by the co-rank of the fundamental group, improving approximation bounds.
New method uses contours of segmented images for X-ray classification.
problem Classifying X-ray images of segmented radiography.
method Develops a new approach for image analysis of multivariate planar curves, addressing alignment issues.
result Demonstrates the robustness and appeal of the proposed method through detection of cardiomegaly and numerical experiments.
We study the soliton flow on the domain of a twistorial harmonic morphism between Riemannian manifolds of dimensions four and three. Assuming real-analyticity, we prove that, for the Gibbons-Hawking construction, any soliton flow is uniquely determined by its restriction to any local section of the corresponding harmon…