Urban development can impact environmental quality and ecosystem services well beyond urban extent. Many methods to map urban areas have been developed and used in the past, but most have simply tried to map existing extent of urban development, and all have been single-scale techniques. The method presented here uses a clustering approach to look beyond the extant urban area at multiple scales...

We propose a new complete method to extract significant description(s) of planar curves according to constant curvature segments. This method is based (i) on a multi-scale segmentation and curve approximation algorithm, defined by two grouping processes (polygonal and constant curvature approximations), leading to a multi-scale covering of the curve, and (ii) on an intraand inter-scale classifi...

Deep learning architecture has been applied in computer vision to learn features in an unsupervised manner. Thousands of features can be achieved in such manner. Furthermore, in some modified architectures, multi-scale features which contain middle layer features and output layer features, can connect to classifier. The classifier is trained using these features to predict the label of input im...

In this paper, we address the problem of learning multi-scale sparse representations of natural images using structured dictionaries. Dictionaries learned by traditional algorithms have two major limitations: lack of structure and fixed size. These methods treat atoms independently from each other, and do not exploit possible relationships between them. Fixed size of atoms restricts the flexibi...

The problem of prediction of finite temperature properties of materials poses great computational challenges. The computational treatment of the multitude of length and time scales involved in determining macroscopic properties has been attempted by several workers with varying degrees of success. This paper will review the recently developed quasicontinuum method which is an attempt to bridge ...

In this paper, we propose a numerical method, the finite difference heterogeneous multi-scale method (FD-HMM), for solving multi-scale parabolic problems. Based on the framework introduced in [Commun. Math. Sci. 1 (1) 87], the numerical method relies on the use of two different schemes for the original equation, at different grid level which allows to give numerical results at a much lower cost...

The viability of the Variational Multi-Scale (VMS), an approach for Large Eddy Simulation (LES), in the context of turbulence control is explored. First, we validate our VMS implementation for a fully-developed turbulent channel. Later, VMS results for opposition control of the turbulent channel flow are compared against available Direct Numerical Simulation (DNS) and LES using dynamic subgrid-...

In order to provide users with the function of navigating across different details of level, ranging from overview screen to detailed views, it is necessary to display these representations with different detail levels at a successive and smoothly transformation order, the existing methods for multi-scale visualization are integrated and extended in the paper, and a new method, named as ‘object...