Image Segmentation by Nonparametric Clustering Based on the Kolmogorov-Smirnov Distance

Pauwels, Eric J.; Frederix, Greet

doi:10.1007/3-540-45053-x_6

Cited by 12 publications

(6 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In clustering, different 1-D clusters correspond to a multi-modal distribution, so clusters can be naturally described as combinations of monotonicity intervals separating local minima of the probability density function; see, e.g., [16], [19], [20].…”

Section: Formulation Of the Problemmentioning

confidence: 99%

Checking If There Exists a Monotonic Function That Is Consistent with the Measurements: An Efficient Algorithm

2005

View full text Add to dashboard Cite

In many problems in science and engineering ranging from astrophysics to geosciences to financial analysis, we know that a physical quantity y depends on the physical quantity x, i.e., y = (x) for some function (x), and we want to check whether this dependence is monotonic. Specifically, finitely many measurements of xi and yi = (xi) have been made, and we want to check whether the results of these measurements are consistent with the monotonicity of (x). An efficient parallelizable algorithm is known for solving this problem when the values xi are known precisely, while the values yi are known with interval uncertainty. In this paper, we extend this algorithm to a more general (and more realistic) situation when both xi and yi are known with interval uncertainty.

show abstract

Section: Formulation Of the Problemmentioning

confidence: 99%

Checking If There Exists a Monotonic Function That Is Consistent with the Measurements: An Efficient Algorithm

2005

View full text Add to dashboard Cite

show abstract

“…The two-sample Kolmogorov-Smirnov (KS) test is one of the most useful and general nonparametric methods for comparing two samples. In other contexts, [40][41][42] the KS test statistic has been used to define distances for the purpose of hierarchical clustering. Borrowing the idea from hypothesis testing, we define the distance between a pair of amino acids by the normalized two-sample KS test statistic (Equation 2) when contrasting their RSA distributions.…”

Section: P C R E P C a R E P A R Ementioning

confidence: 99%

Roles of Solvent Accessibility and Gene Expression in Modeling Protein Sequence Evolution

Wang

et al. 2015

Evol Bioinform Online

View full text Add to dashboard Cite

Models of protein evolution tend to ignore functional constraints, although structural constraints are sometimes incorporated. Here we propose a probabilistic framework for codon substitution that evaluates joint effects of relative solvent accessibility (RSA), a structural constraint; and gene expression, a functional constraint. First, we explore the relationship between RSA and codon usage at the genomic scale as well as at the individual gene scale. Motivated by these results, we construct our framework by determining how probable is an amino acid, given RSA and gene expression, and then evaluating the relative probability of observing a codon compared to other synonymous codons. We come to the biologically plausible conclusion that both RSA and gene expression are related to amino acid frequencies, but, among synonymous codons, the relative probability of a particular codon is more closely related to gene expression than RSA. To illustrate the potential applications of our framework, we propose a new codon substitution model. Using this model, we obtain estimates of 2N s, the product of effective population size N, and relative fitness difference of allele s. For a training data set consisting of human proteins with known structures and expression data, 2N s is estimated separately for synonymous and nonsynonymous substitutions in each protein. We then contrast the patterns of synonymous and nonsynonymous 2N s estimates across proteins while also taking gene expression levels of the proteins into account. We conclude that our 2N s estimates are too concentrated around 0, and we discuss potential explanations for this lack of variability.

show abstract

“…thresholds that are dictated by the structure apparent in the data [25]. To be more precise, assume that we have a numerical image feature x that can be computed at each of the n pixel in the image (e.g.…”

Section: Fig 4: Feature Detection Stepsmentioning

confidence: 99%

The role of high-level and low-level features in style-based retrieval and generation of multimedia presentations

Nack

Windhouwer

Hardman

et al. 2001

New Review of Hypermedia and Multimedia

View full text Add to dashboard Cite

In this article we argue that the automatic generation of dynamic multimedia presentation requires both low-level collections of objective measurements for media units representing prototypical style elements, and high-level conceptual descriptions supporting contextual and presentational requirements. Only the combination of both facilitates the retrieval of adequate material and its user-centred presentation. We discuss the problems of visual signification for images in dynamic systems and explain how a combined approach can help overcome such problems. We then propose an architecture for such a system and present its applicability for a museum-oriented multimedia system with a working example. KeywordsMultimedia semantics, feature grammars, style-based multimedia presentation generation, multimedia retrieval INTRODUCTIONOver the last decade, museums have been contributing to the information revolution by digitising their collections and providing access to them for the general public. Currently, many sophisticated and visually pleasing environments, such as exhibitions in virtual galleries, art collections and presentations of different cultural artefacts, are available. A problem with these environments is that they are handcrafted. In nearly all cases, they lack adaptive [8] or adaptable qualities [28], which could otherwise facilitate the adjustment of the multimedia presentation to the specific context of an individual user. For overcoming these problems, various attempts to explore and develop innovative presentation techniques are described by [1,2,6,20,36]. These approaches facilitate the synthesis of multimedia documents and plan how this material is presented to various users. The underlying assumption of these systems, however, is that all material and its combinatorial possibilities are known.In dynamic environments, such as web-based museums, where neither the individual user requirements nor the requested material can be predicted in advance a top-down planning approach is not sufficient. Instead, we claim that a system must be provided with knowledge of simple codes, i.e. collections of objective measurements for media units [10,19] representing prototypical style elements, which are combined with high-level conceptual descriptions [31] supporting contextual and presentational requirements. Using such a combinatorial approach it is possible to establish conceptual presentations that support a better understanding of art, so that the system can find satisfactory solutions for upcoming questions (e.g. based on the content of an image), misunderstandings (rearrangement of the material) or non-understanding (creation of a new sequence).The mapping of high-level conceptual structures with low-level feature descriptions as an essential mechanism to enhance the automatic generation of dynamic style-oriented multimedia environments is part of the methodology followed in the Cuypers project [34]. The aim of this work is to improve existing search techniques on category and image features to facil...

show abstract

Image Segmentation by Nonparametric Clustering Based on the Kolmogorov-Smirnov Distance

Cited by 12 publications

References 10 publications

Checking If There Exists a Monotonic Function That Is Consistent with the Measurements: An Efficient Algorithm

Checking If There Exists a Monotonic Function That Is Consistent with the Measurements: An Efficient Algorithm

Roles of Solvent Accessibility and Gene Expression in Modeling Protein Sequence Evolution

The role of high-level and low-level features in style-based retrieval and generation of multimedia presentations

Contact Info

Product

Resources

About