Search results for "resolution."
showing 10 items of 1825 documents
Towards High Resolution Computational Models of the Cardiac Conduction System: A Pipeline for Characterization of Purkinje-Ventricular-Junctions
2011
The cardiac conduction system (CCS) has been in the spot light of the clinical and modeling community in recent years because of its fundament role in physiology and pathophysiology of the heart. Experimental research has focused mainly on investigating the electrical properties of the Purkinje-ventricular-junctions (PVJs). The structure of the PVJs has only been described through schematic drawings but not thoroughly studied. In this work confocal microscopy was used with the aim of three-dimensional characterization of PVJs. Adult rabbit hearts were labeled with fluorescent dyes, imaged with confocal microscopy and Purkinje fibers differentiated from other cardiac tissue by their lack of …
On the stability of spline-collocation methods of multivalue type
1987
In this paper the general classV of spline-collocation methods for first order systems of ordinary differential equations is investigated. The methods can in part be regarded as so-called multivalue methods. This type contains the generalized singly-implicit methods treated by Butcher.
A low power and high resolution data logger for submarine seismic monitoring
2010
The design, implementation and characterization of a digital waveform recorder for ocean bottom seismic monitoring is here reported. The system is capable of synchronously acquiring, and logging on a flash memory bank, four high resolution signals. Thanks to a very careful design of the system architecture and by using robust digital signal processing techniques, two main conflicting issues have been addressed: a high dynamic range, better than 120 dB, usually obtained with high energy demanding converters, and a power consumption as low as 250 mW, hence allowing to easily increase the time of a continuous submarine monitoring session up to 3 months.
Modular Strategies for Recursive Game Graphs
2006
AbstractMany problems in formal verification and program analysis can be formalized as computing winning strategies for two-player games on graphs. In this paper, we focus on solving games in recursive game graphs which can model the control flow in sequential programs with recursive procedure calls. While such games can be viewed as the pushdown games studied in the literature, the natural notion of winning in our framework requires the strategies to be modular with only local memory; that is, resolution of choices within a module does not depend on the context in which the module is invoked, but only on the history within the current invocation of the module. While reachability in (global…
Integer Weighted Regression Tsetlin Machines
2020
The Regression Tsetlin Machine (RTM) addresses the lack of interpretability impeding state-of-the-art nonlinear regression models. It does this by using conjunctive clauses in propositional logic to capture the underlying non-linear frequent patterns in the data. These, in turn, are combined into a continuous output through summation, akin to a linear regression function, however, with non-linear components and binary weights. However, the resolution of the RTM output is proportional to the number of clauses employed. This means that computation cost increases with resolution. To address this problem, we here introduce integer weighted RTM clauses. Our integer weighted clause is a compact r…
Experiencing with electronic image stabilization and PRNU through scene content image registration
2021
Abstract This paper explores content-based image registration as a means of dealing with and understanding better Electronic Image Stabilization (EIS) in the context of Photo Response Non-Uniformity (PRNU) alignment. A novel and robust solution to extrapolate the transformation relating the different image output formats for a given device model is proposed. This general approach can be adapted to specifically extract the scale factor (and, when appropriate, the translation) so as to align native resolution images to video frames, with or without EIS on, and proceed to compare PRNU patterns. Comparative evaluations show that the proposed approach outperforms those based on brute-force and p…
On the application of the generalized means to construct multiresolution schemes satisfying certain inequalities proving stability
2021
Multiresolution representations of data are known to be powerful tools in data analysis and processing, and they are particularly interesting for data compression. In order to obtain a proper definition of the edges, a good option is to use nonlinear reconstructions. These nonlinear reconstruction are the heart of the prediction processes which appear in the definition of the nonlinear subdivision and multiresolution schemes. We define and study some nonlinear reconstructions based on the use of nonlinear means, more in concrete the so-called Generalized means. These means have two interesting properties that will allow us to get associated reconstruction operators adapted to the presence o…
AUTOMATIC QUALITY ENHANCEMENT AND NERVE FIBRE LAYER ARTEFACTS REMOVAL IN RETINA FUNDUS IMAGES BY OFF AXIS IMAGING
2011
International audience; Retinal fundus images acquired with non-mydriatic digital fundus cameras are a versatile tool for the diagnosis of various retinal diseases. Even with relative ease of use, the images produced sometimes suffer from reflectance artefacts mainly due to the nerve fibre layer (NFL) or camera lens related reflections. We propose a technique that employs multiple fundus images to obtain a single higher quality image without these reflectance artefacts, which also compensates for a suboptimal illumination. The removal of bright artefacts, can have great benefits for the reduction of false positives in the detection of retinal lesions by automatic systems or manual inspectio…
A new Adaptive and Progressive Image Transmission Approach using Function Superpositions
2010
International audience; We present a novel approach to adaptive and progressive image transmission, based on the decomposition of an image into compositions and superpositions of monovariate functions. The monovariate functions are iteratively constructed and transmitted, one after the other, to progressively reconstruct the original image: the progressive transmission is performed directly in the 1D space of the monovariate functions and independently of any statistical properties of the image. Each monovariate function contains only a fraction of the pixels of the image. Each new transmitted monovariate function adds data to the previously transmitted monovariate functions. After each tra…
A Comparison of Advanced Regression Algorithms for Quantifying Urban Land Cover
2014
Quantitative methods for mapping sub-pixel land cover fractions are gaining increasing attention, particularly with regard to upcoming hyperspectral satellite missions. We evaluated five advanced regression algorithms combined with synthetically mixed training data for quantifying urban land cover from HyMap data at 3.6 and 9 m spatial resolution. Methods included support vector regression (SVR), kernel ridge regression (KRR), artificial neural networks (NN), random forest regression (RFR) and partial least squares regression (PLSR). Our experiments demonstrate that both kernel methods SVR and KRR yield high accuracies for mapping complex urban surface types, i.e., rooftops, pavements, gras…