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A variational level set model combining with local Gaussian fitting and Markov random field regularization
To effectively and accurately segment images in the presence of intensity inhomogeneity and noise, a variational level set model based on maximum a...
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Re-initialization-Free Level Set Method via Molecular Beam Epitaxy Equation Regularization for Image Segmentation
Variational level set method has become a powerful tool in image segmentation due to its ability to handle complex topological changes and maintain...
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A variational level set model with closed-form solution for bimodal image segmentation
In this work, we present a variational level set model with closed–form solution via combining with the fuzzy clustering method for robust and...
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Multimodal variational contrastive learning for few-shot classification
The effectiveness of metric-based few-shot learning methods heavily relies on the discriminative ability of the prototypes and feature embeddings of...
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Target positioning method based on B-spline level set and GC Yolo-v3
In industrial applications, mobile robot navigation involves autonomously moving towards specific target areas. Visual sensors are commonly used to...
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Research on Image Segmentation Algorithm Based on Level Set
Digital image processing has garnered significant attention and extensive research in both civilian and military domains. Image segmentation serves...
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A level set model with shape prior constraint for intervertebral disc MRI image segmentation
Accurate intervertebral disc image segmentation is necessary for further treatment. However, existing methods are difficult to segment due to the...
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A generalized cyclic iterative method for solving variational inequalities over the solution set of a split common fixed point problem
We introduce a new generalized cyclic iterative method for finding solutions of variational inequalities over the solution set of a split common...
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Transformer-based Denoising Adversarial Variational Entity Resolution
Entity resolution (ER), precisely identifying different representations of the same real-world entities, is critical for data integration. The ER...
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New algorithm using an adaptive level set model applied to hippocampus segmentation and volume calculation in MRI images
The hippocampus is known as one of the most important brain structures since the change in its volume is an early symptom of many diseases such as...
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An automatic MRI brain image segmentation technique using edge–region-based level set
Digital transformation has brought radical changes in several domains. Particularly, image processing techniques have been generally used in medical,...
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Stochastic variational inference for GARCH models
Stochastic variational inference algorithms are derived for fitting various heteroskedastic time series models. We examine Gaussian, t, and skewed t...
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VNAS: Variational Neural Architecture Search
Differentiable neural architecture search delivers point estimation to the optimal architecture, which yields arbitrarily high confidence to the...
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Adaptive contrast enhancement for underwater image using imaging model guided variational framework
Underwater images are typically characterized by blurry details, poor contrast, and color distortions owing to absorption and scattering effects,...
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Scene Text Detection with Box Supervision and Level Set Evolution
For arbitrarily-shaped scene text detection, most existing methods require expensive polygon-level annotations for supervised training. In order to...
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Variational satisfiability solving: efficiently solving lots of related SAT problems
Incremental satisfiability (SAT) solving is an extension of classic SAT solving that enables solving a set of related SAT problems by identifying and...
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A Segmentation Based Robust Fractional Variational Model for Motion Estimation
In this paper, we introduce a nonlinear robust fractional order variational framework for motion estimation from image sequences (video)....
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Variational Perspective on Fair Edge Prediction
Algorithmic fairness has been of great interest in the machine learning community and more recently in the graph context. In this paper, we address...
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Variational Gaussian topic model with invertible neural projections
Neural topic models have triggered a surge of interest in extracting topics from text automatically since they avoid the sophisticated derivations in...
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Box-Supervised Instance Segmentation with Level Set Evolution
In contrast to the fully supervised methods using pixel-wise mask labels, box-supervised instance segmentation takes advantage of the simple box...