270 research outputs found
Traditional Cultural Districts: An Opportunity for Alaska Tribes to Protect Subsistence Rights and Traditional Lands
Alaska tribes have limited control over their traditional lands and waters. Tribes may increase their influence through a Traditional Cultural District designation under Section 106 of the National Historic Preservation Act. This designation does not stop development, but requires federal agencies to consult with tribes regarding potential development that may impact the district. The consultation right applies regardless of whether a tribe owns or has formally designated the district. In Alaska, where no Traditional Cultural Districts exist as of 2014, there is potential for designating large areas of land or water that correspond to the range of traditionally important species
Assessing the financial potential of the company
In this position paper, we seek to extend the layered perception-action paradigm for on-line learning such that it includes an explicit symbolic processing capability. By incorporating symbolic processing at the apex of the perception action hierarchy in this way, we ensure that abstract symbol manipulation is fully grounded, without the necessity of specifying an explicit representational framework. In order to carry out this novel interfacing between symbolic and sub-symbolic processing, it is necessary to embed fuzzy rst-order logic theorem proving within a variational framework. The online learning resulting from the corresponding Euler-Lagrange equations establishes an extended adaptability compared to the standard subsumption architecture. We discuss an application of this approach within the eld of advanced driver assistance systems, demonstrating that a closed-form solution to the Euler Lagrange optimization problem is obtainable for simple cases. DIPLEC
Multiscale optical flow computation from the monogenic signal
National audienceWe have developed an algorithm for the estimation of cardiac motion from medical images. The algorithm exploits monogenic signal theory, recently introduced as an N-dimensional generalization of the analytic signal. The displacement is computed locally by assuming the conservation of the monogenic phase over time. A local affine displacement model replaces the standard translation model to account for more complex motions as contraction/expansion and shear. A coarse-to-fine B-spline scheme allows a robust and effective computation of the models parameters and a pyramidal refinement scheme helps handle large motions. Robustness against noise is increased by replacing the standard pointwise computation of the monogenic orientation with a more robust least-squares orientation estimate. This paper reviews the results obtained on simulated cardiac images from different modalities, namely 2D and 3D cardiac ultrasound and tagged magnetic resonance. We also show how the proposed algorithm represents a valuable alternative to state-of-the-art algorithms in the respective fields
The economic and accounting content of fixed assets
This book presents a mathematical methodology for image analysis tasks at the edge of current research, including anisotropic diffusion filtering of tensor fields. Instead of specific applications, it explores methodological structures on which they are built.DIPLECS, GARNICS, NACI
Instantaneous frequency and amplitude of complex signals based on quaternion Fourier transform
The ideas of instantaneous amplitude and phase are well understood for
signals with real-valued samples, based on the analytic signal which is a
complex signal with one-sided Fourier transform. We extend these ideas to
signals with complex-valued samples, using a quaternion-valued equivalent of
the analytic signal obtained from a one-sided quaternion Fourier transform
which we refer to as the hypercomplex representation of the complex signal. We
present the necessary properties of the quaternion Fourier transform,
particularly its symmetries in the frequency domain and formulae for
convolution and the quaternion Fourier transform of the Hilbert transform. The
hypercomplex representation may be interpreted as an ordered pair of complex
signals or as a quaternion signal. We discuss its derivation and properties and
show that its quaternion Fourier transform is one-sided. It is shown how to
derive from the hypercomplex representation a complex envelope and a phase.
A classical result in the case of real signals is that an amplitude modulated
signal may be analysed into its envelope and carrier using the analytic signal
provided that the modulating signal has frequency content not overlapping with
that of the carrier. We show that this idea extends to the complex case,
provided that the complex signal modulates an orthonormal complex exponential.
Orthonormal complex modulation can be represented mathematically by a polar
representation of quaternions previously derived by the authors. As in the
classical case, there is a restriction of non-overlapping frequency content
between the modulating complex signal and the orthonormal complex exponential.
We show that, under these conditions, modulation in the time domain is
equivalent to a frequency shift in the quaternion Fourier domain. Examples are
presented to demonstrate these concepts
Динамика интеграционных процессов ЕАЭС
Проведено исследование динамики интеграционных процессов и факторов, их определяющих. Отмечено, что ключевым моментом интеграции стран ЕАЭС является углубление кооперационных связей и формирование региональных цепочек добавленной стоимости
Математична модель контактного з’єднання метало-пластмасових циліндричних оболонок
We consider alpha scale spaces, a parameterized class (alpha is an element of (0, 1]) of scale space representations beyond the well-established Gaussian scale space, which are generated by the alpha-th power of the minus Laplace operator on a bounded domain using the Neumann boundary condition. The Neumann boundary condition ensures that there is no grey-value flux through the boundary. Thereby no artificial grey-values from outside the image affect the evolution proces, which is the case for the alpha scale spaces on an unbounded domain. Moreover, the connection between the a scale spaces which is not trivial in the unbounded domain case, becomes straightforward: The generator of the Gaussian semigroup extends to a compact, self-adjoint operator on the Hilbert space L-2(Omega) and therefore it has a complete countable set of eigen functions. Taking the alpha-th power of the Gaussian generator simply boils down to taking the alpha-th power of the corresponding eigenvalues. Consequently, all alpha scale spaces have exactly the same eigen-modes and can be implemented simultaneously as scale dependent Fourier series. The only difference between them is the (relative) contribution of each eigen-mode to the evolution proces. By introducing the notion of (non-dimensional) relative scale in each a scale space, we are able to compare the various alpha scale spaces. The case alpha = 0.5, where the generator equals the square root of the minus Laplace operator leads to Poisson scale space, which is at least as interesting as Gaussian scale space and can be extended to a (Clifford) analytic scale space
Defining the essence of innovation how important terms in promoting of transformation processes in Ukraine
Feature hierarchies are essential to many visual object recognition systems and are well motivated by observations in biological systems. The present paper proposes an algorithm to incrementally compute feature hierarchies. The features are represented as estimated densities, using a variant of local soft histograms. The kernel functions used for this estimation in conjunction with their unitary extension establish a tight frame and results from framelet theory apply. Traversing the feature hierarchy requires resampling of the spatial and the feature bins. For the resampling, we derive a multi-resolution scheme for quadratic spline kernels and we derive an optimization algorithm for the upsampling. We complement the theoretic results by some illustrative experiments, consideration of convergence rate and computational efficiency.DIPLECSGARNICSELLII
LSOTB-TIR:A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark
In this paper, we present a Large-Scale and high-diversity general Thermal
InfraRed (TIR) Object Tracking Benchmark, called LSOTBTIR, which consists of an
evaluation dataset and a training dataset with a total of 1,400 TIR sequences
and more than 600K frames. We annotate the bounding box of objects in every
frame of all sequences and generate over 730K bounding boxes in total. To the
best of our knowledge, LSOTB-TIR is the largest and most diverse TIR object
tracking benchmark to date. To evaluate a tracker on different attributes, we
define 4 scenario attributes and 12 challenge attributes in the evaluation
dataset. By releasing LSOTB-TIR, we encourage the community to develop deep
learning based TIR trackers and evaluate them fairly and comprehensively. We
evaluate and analyze more than 30 trackers on LSOTB-TIR to provide a series of
baselines, and the results show that deep trackers achieve promising
performance. Furthermore, we re-train several representative deep trackers on
LSOTB-TIR, and their results demonstrate that the proposed training dataset
significantly improves the performance of deep TIR trackers. Codes and dataset
are available at https://github.com/QiaoLiuHit/LSOTB-TIR.Comment: accepted by ACM Mutlimedia Conference, 202
- …