pinecone/core-2020-05-10-deduplication huggingface dataset:
Binary Partition Trees-based spectral-spatial permutation ordering

International audienceMathematical Morphology (MM) is founded on the mathematical branch of Lattice Theory. Morphological operations can be described as mappings between complete lattices, and complete lattices are a type of partially-ordered sets (poset). Thus, the most elementary requirement to define morphological operators on a data domain is to establish an ordering of the data. MM has been very successful defining image operators and filters for binary and gray-scale images, where it can take advantage of the natural ordering of the sets {0, 1} and Z +. For multivariate data, i.e. RGB or hyperspectral images, other orderings such as reduced orderings (R-orderings) have been proposed. Anyway, all these orderings are based solely on sorting the spectral set of values. Here, we propose to define an ordering based on both, the spectral and the spatial information, by means of a binary partition tree (BPT) representation of images. This novel ordering takes into account not only the spectral ordering but also the hierarchies of spatial structures encoded in the BPT
Shape-based analysis on component-graphs for multivalued image processing

International audienceThe extension of mathematical morphology to multivalued images is an important issue. This is particularly true in the context of connected operators based on morphological hierarchies, which aim to provide efficient image filtering and segmentation tools in various application fields, e.g. (bio)medical imaging, remote sensing, or astronomy. In this article, we propose a preliminary study that describes how two notions recently introduced for connected filtering, namely component-graphs (that extend component-trees from a spectral point of view) and shaping (that extend component-trees from a conceptual point of view) can be associated for the effective processing of multivalued images. Structural, algo-rithmic and experimental developments are proposed. This study opens the way to new paradigms for connected filtering based on hierarchies
Evaluation of morphological hierarchies for supervised segmentation

International audienceWe propose a quantitative evaluation of morphological hierarchies (quasi-flat zones, constraint connectivity, watersheds, observation scale) in a novel framework based on the marked segmentation problem. We created a set of automatically generated markers for the one object image datasets of Grabcut and Weizmann. In order to evaluate the hierarchies , we applied the same segmentation strategy by combining several parameters and markers. Our results, which shows important differences among the considered hierarchies, give clues to understand the behaviour of each method in order to choose the best one for a given application. The code and the marker datasets are available online
When Convex Analysis Meets Mathematical Morphology on Graphs

International audienceIn recent years, variational methods, i.e., the formulation of problems under optimization forms, have had a great deal of success in image processing. This may be accounted for by their good performance and versatility. Conversely, mathematical morphology (MM) is a widely recognized methodology for solving a wide array of image processing-related tasks. It thus appears useful and timely to build bridges between these two fields. In this article, we propose a variational approach to implement the four basic, structuring element-based operators of MM: dilation, erosion, opening, and closing. We rely on discrete calculus and convex analysis for our formulation. We show that we are able to propose a variety of continuously varying operators in between the dual extremes, i.e., between erosions and dilation; and perhaps more interestingly between openings and closings. This paves the way to the use of morphological operators in a number of new applications
( max , min )-convolution and Mathematical Morphology

International audienceA formal denition of morphological operators in (max, min)-algebra is introduced and their relevant properties from an algebraic viewpoint are stated. Some previous works in mathematical morphology have already encountered this type of operators but a systematic study of them has not yet been undertaken in the morphological literature. It is shown in particular that one of their fundamental property is the equivalence with level set processing using Minkowski addition and subtraction. Theory of viscosity solutions of the Hamilton-Jacobi equation with Hamiltonians containing u and Du is summarized, in particular, the corresponding Hopf-Lax-Oleinik formulas as (max, min)-operators. Links between (max, min)-convolutions and some previous approaches of unconventional morphology, in particular fuzzy morphology and viscous morphology, are reviewed
Morphological PDE and dilation/erosion semigroups on length spaces

International audienceThis paper gives a survey of recent research on Hamilton-Jacobi partial dierential equations (PDE) on length spaces. This theory provides the background to formulate morphological PDEs for processing data and images supported on a length space, without the need of a Riemmanian structure. We first introduce the most general pair of dilation/erosion semigroups on a length space, whose basic ingredients are the metric distance and a convex shape function. The second objective is to show under which conditions the solution of a morphological PDE in the length space framework is equal to the dilation/erosion semigroups
How to Make nD Functions Digitally Well-Composed in a Self-dual Way

International audienceLatecki et al. introduced the notion of 2D and 3D well-composed images, i.e., a class of images free from the " connectivities paradox " of digital topology. Unfortunately natural and synthetic images are not a priori well-composed. In this paper we extend the notion of " digital well-composedness " to nD sets, integer-valued functions (gray-level images), and interval-valued maps. We also prove that the digital well-composedness implies the equivalence of connectivities of the level set components in nD. Contrasting with a previous result stating that it is not possible to obtain a discrete nD self-dual digitally well-composed function with a local interpolation, we then propose and prove a self-dual discrete (non-local) interpolation method whose result is always a digitally well-composed function. This method is based on a sub-part of a quasi-linear algorithm that computes the morphological tree of shapes
Ranking orientation responses of path operators: Motivations, choices and algorithmics

International audienceA new morphological operator, namely RORPO (Ranking Orientation Responses of Path Operators), was recently introduced as a semi-global, morphological alternative to the local, Hessian-based operators for thin structure filtering in 3D images. In this context, a previous study has already provided experimental proof of its relevance by comparison to such differential operators. In this article, we present a methodological study of RORPO, which completes the presentation of this new morphological filter. In particular, we expose the motivations of RORPO with respect to previous morphological strategies; we present algo-rithmic developments of this filter and the underlying robust path operator; and we discuss computational issues related to parametricity and time efficiency. We conclude this study by a discussion on the methodological and applicative potentiality of RORPO in various fields of image processing and analysis
Efficient Computation of Attributes and Saliency Maps on Tree-Based Image Representations

International audienceTree-based image representations are popular tools for many applications in mathematical morphology and image processing. Classically , one computes an attribute on each node of a tree and decides whether to preserve or remove some nodes upon the attribute function. This attribute function plays a key role for the good performance of tree-based applications. In this paper, we propose several algorithms to compute efficiently some attribute information. The first one is incremen-tal computation of information on region, contour, and context. Then we show how to compute efficiently extremal information along the contour (e.g., minimal gradient's magnitude along the contour). Lastly, we depict computation of extinction-based saliency map using tree-based image representations. The computation complexity and the memory cost of these algorithms are analyzed. To the best of our knowledge, except information on region, none of the other algorithms is presented explicitly in any state-of-the-art paper
A watershed algorithm progressively unveiling its optimality

International audienceIn 1991 I described a particularly simple and elegant water-shed algorithm, where the ooding a topographic surface was scheduled by a hierarchical queue. In 2004 the watershed line has been described as the skeleton by zone of inuence for the topographic distance. The same algorithm still applies. In 2012 I dened a new distance based on a lexicographic ordering of the downstream paths leading each node to a regional minimum. Without changing a iota, the same algorithm does the job
Inner-Cheeger Opening and Applications

International audienceThe aim of this paper is to study an optimal opening in the sense of minimize the relationship perimeter over area. We analyze theoretical properties of this opening by means of classical results from variational calculus. Firstly, we explore the optimal radius as attribute in morphological attribute filtering for grey scale images. Secondly, an application of this optimal opening that yields a decomposition into meaningful parts in the case of binary image is explored. We provide different examples of 2D, 3D images and mesh-points datasets
Multitemporal Land Use/Land Cover Change Detection for the Batena Watershed, Rift Valley Lakes Basin, Ethiopia

A majorityof therural population in Ethiopiadepends on agriculture. Land use changes during the past couple of decades are mostly linked to agricultural development attributed to factors such as population pressure and environmental changes. Mapping land use/land cover (LULC) to analyze the type, rate, and extent of changes in land use patterns has far reaching significance for policy/decision makers and resource managers to provoke the wide range of applications at regional scales for erosion, landslide, land planning, forest management, and ecosystem conservation. The focus of this chapter is to depict quick and practical approaches to generate spatially and temporally quantified information on land cover dynamics using high-resolution satellite images for the years (1973–2008) in Batena watershed and its environs in southwestern Ethiopia. To quantify the magnitude of LULC change, supervised classification technique was applied using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images employing Bayesian maximum likelihood classifier (MLC) with the aid of ground truth training sites. A majority/minority analysis was used for smoothing the classification results and the accuracy of image classification was carried out by means of a confusion matrix generated through geographic information system (GIS) overlay of the classified maps and the test samples. The classification accuracy was further verified by the strong kappa statistical estimate of more than 90 % as a measure of overall agreement between image and reference data. The final output of remote sensing imagery revealed five land cover classes: Grazing land, bush land, mixed forest, dominantly cultivated agricultural land, and water body. It has been discovered that, there were more active LULC change processes in the area in the first study period (1973–1984) than the second study period (1984–1995) and the third study period (1995–2003). On the other hand, areal extent of cultivated and uncultivated agricultural land has been on a steady decline from 39.7 % in 1995 to 41.4 % in 2003 and a mere 50.1 % in 2008. In the first period, nearly half of the landscape underwent land cover change with more than 17 % of the entire landscape experiencing agricultural expansion. In the second period, the extent of the changes was limited to less than 1/3 of the total area with a smaller amount of agricultural area expansion than before. Though the rate of land cover change was observed to vary across the three periods of study, a general decline of forest cover and amplified increase of agricultural lands of more than 41.7 % was found in the area.Full Tex
Ranking Entities in the Age of Two Webs, an Application to Semantic
  Snippets

The advances of the Linked Open Data (LOD) initiative are giving rise to a
more structured Web of data. Indeed, a few datasets act as hubs (e.g., DBpedia)
connecting many other datasets. They also made possible new Web services for
entity detection inside plain text (e.g., DBpedia Spotlight), thus allowing for
new applications that can benefit from a combination of the Web of documents
and the Web of data. To ease the emergence of these new applications, we
propose a query-biased algorithm (LDRANK) for the ranking of web of data
resources with associated textual data. Our algorithm combines link analysis
with dimensionality reduction. We use crowdsourcing for building a publicly
available and reusable dataset for the evaluation of query-biased ranking of
Web of data resources detected in Web pages. We show that, on this dataset,
LDRANK outperforms the state of the art. Finally, we use this algorithm for the
construction of semantic snippets of which we evaluate the usefulness with a
crowdsourcing-based approach
PADTUN - using semantic technologies in tunnel diagnosis and maintenance domain

YesA Decision Support System (DSS) in tunnelling domain deals with identifying pathologies based on disorders present in various tunnel portions and contextual factors affecting a tunnel. Another key area in diagnosing pathologies is to identify regions of interest (ROI). In practice, tunnel experts intuitively abstract regions of interest by selecting tunnel portions that are susceptible to the same types of pathologies with some distance approximation. This complex diagnosis process is often subjective and poorly scales across cases and transport structures. In this paper, we introduce PADTUN system, a working prototype of a DSS in tunnelling domain using semantic technologies. Ontologies are developed and used to capture tacit knowledge from tunnel experts. Tunnel inspection data are annotated with ontologies to take advantage of inferring capabilities offered by semantic technologies. In addition, an intelligent mechanism is developed to exploit abstraction and inference capabilities to identify ROI. PADTUN is developed in real-world settings offered by the NeTTUN EU Project and is applied in a tunnel diagnosis use case with Société Nationale des Chemins de Fer Français (SNCF), France. We show how the use of semantic technologies allows addressing the complex issues of pathology and ROI inferencing and matching experts’ expectations of decision support
Parareal for diffusion problems with space- and time-dependent
  coefficients

For the time-parallel Parareal method, there exists both numerical and
analytical proof that it converges very well for diffusive problems like the
heat equation. Many applications, however, do not lead to simple homogeneous
diffusive scenarios but feature strongly inhomogeneous and possibly anisotropic
coefficients. The paper presents results from a numerical study of how space-
and time-dependent coefficients in a diffusion setup affect Parareal's
convergence behaviour. It is shown that, for the presented examples,
non-constant diffusion coefficients have only marginal influence on how fast
Parareal converges. Furthermore, an example is shown that illustrates how for
linear problems the maximum singular value of the Parareal iteration matrix can
be used to estimate convergence rates
Inexact spectral deferred corrections

Spectral deferred correction (SDC) methods are an attractive approach to
iteratively computing collocation solutions to an ODE by performing so-called
sweeps with a low-order time stepping method. SDC allows to easily construct
high order split methods where e.g. stiff terms of the ODE are treated
implicitly. This requires the solution to full accuracy of multiple linear
systems of equations during each sweep, e.g. with a multigrid method. In this
paper, we present an inexact variant of SDC, where each solve of a linear
system is replaced by a single multigrid V-cycle and thus significantly reduces
the cost for each sweep. For the investigated examples, this strategy results
only in a small increase of the number of required sweeps and we demonstrate
that "inexact spectral deferred corrections" can provide a dramatic reduction
of the overall number of multigrid V-cycles required to complete an SDC time
step
Robin-Neumann schemes for incompressible fluid-structure interaction

International audienceMathematical problems involving the coupling of an incompressible viscous flow with an elastic structure appear in a large variety of engineering fields. This problem is considered here within a heterogenous domain decomposition framework, with the aim of using independent well-suited solvers for the fluid and the solid. One of the main difficulties that have to be faced under this approach is that the coupling can be very stiff. In particular, traditional Dirichlet-Neumann explicit coupling methods, which solve for the fluid (Dirichlet) and for the solid (Neumann) only once per time-step, are unconditionally unstable whenever the amount of added-mass effect in the system is large. Typically this happens when the fluid and solid densities are close and the fluid domain is slender, as in hemodynamic applications. This explains, in part, the tremendous amount of work devoted over the last decade to the development of alternative coupling paradigms. In this paper we will review several explicit coupling procedures recently reported in the literature and present some new developments. The common feature of these methods is that they are based on Robin-Neumann transmission conditions, whose nature depends on the thin- or thick-walled character of the structure
Keynote talk: from analog to digital, fictive vs. documentary: an ongoing journey

This talk will focus upon a personal update of my sojourn as an artist/academician - a journey that has led me from the analog to the electronic medium spanning a timeline of 30 odd years. The exploration, still in progress, will start with city planning, architecture and photography where I acquired, and developed my analog skills. Following this, I will focus on my encounter with the digital revolution, right at a time when the foundations were being laid at one of the leading institutions of the world. I will then ponder on the possible common grounds between analog/digital also by bringing in notions such as serendipity, surprise, uncertainty, inadvertence that lie at the heart of my creative practice. These will constitute the grounds upon which I base my computational art experimentations and my academic research on various transformations in contemporary aesthetics that I believe arose out of digital creativity. Since my main visualization area is photography; indispensable conceptual components such as representation, real, surreal, objectivity, subjectivity, construct will be mentioned and linked to an empirical process based practice.\ud
In addition to investigations on possible relations between art and engineering, I will also reveal my cultural, social, political stance in the light of issues like local vs. global and rhizomatic vs. hierarchic. I will then conclude with my recent concentration on documentary work, after numerous fictive constructions in the digital realm. My objective is to emphasize participatory, collective culture and history making by taking advantage of the democratization brought by ubiquitous mobile imaging and social media communication
TrafficGen: A Flexible Tool For Informing Agent-Based Traffic Simulations With Open Data

ISBN 978-3-319-18943-7International audienceMulti-Agent Systems have been widely used for traffic simulation. The modeling of individuals allows indeed to introduce a behavioral diversity which is crucial to obtain realistic simulation outcomes. The recent growth of open geographical databases and related flow information provides an opportunity for enhancing traffic simulators with data automatically retrieved from the real world and updated regularly. We present here TrafficGen, a highly modular platform based on the integration of such open data within a library of rule-based behaviors, in order to provide a versatile decision support tool in traffic
Nonlinear Lattice Waves in Random Potentials

Localization of waves by disorder is a fundamental physical problem
encompassing a diverse spectrum of theoretical, experimental and numerical
studies in the context of metal-insulator transition, quantum Hall effect,
light propagation in photonic crystals, and dynamics of ultra-cold atoms in
optical arrays. Large intensity light can induce nonlinear response, ultracold
atomic gases can be tuned into an interacting regime, which leads again to
nonlinear wave equations on a mean field level. The interplay between disorder
and nonlinearity, their localizing and delocalizing effects is currently an
intriguing and challenging issue in the field. We will discuss recent advances
in the dynamics of nonlinear lattice waves in random potentials. In the absence
of nonlinear terms in the wave equations, Anderson localization is leading to a
halt of wave packet spreading.
  Nonlinearity couples localized eigenstates and, potentially, enables
spreading and destruction of Anderson localization due to nonintegrability,
chaos and decoherence. The spreading process is characterized by universal
subdiffusive laws due to nonlinear diffusion. We review extensive computational
studies for one- and two-dimensional systems with tunable nonlinearity power.
We also briefly discuss extensions to other cases where the linear wave
equation features localization: Aubry-Andre localization with quasiperiodic
potentials, Wannier-Stark localization with dc fields, and dynamical
localization in momentum space with kicked rotors.Comment: 45 pages, 19 figure
Watermarking capacity control for dynamic payload embedding

Despite significant improvements in capacity-distortion performance, a computationally efficient capacity control is still lacking in the recent watermarking schemes. In this paper, we propose an efficient capacity control framework to substantiate the notion of watermarking capacity control to be the process of maintaining “acceptable” distortion and running time, while attaining the required capacity. The necessary analysis and experimental results on the capacity control are reported to address practical aspects of the watermarking capacity problem, in dynamic (size) payload embedding