Multi-Resolution Algorithm Research Papers - Academia.edu (original) (raw)

In this paper, natural convection of non-Newtonian fluid flow between two infinite parallel vertical plates is studied using interpolation scaling functions based on the Galerkin method. To do so, the governing equations are reduced to a... more

In this paper, natural convection of non-Newtonian fluid flow between two infinite parallel vertical plates is studied using interpolation scaling functions based on the Galerkin method.
To do so, the governing equations are reduced to a set of ordinary differential equations considering both pure and nano-fluid flow. For a highly accurate connection between functions
and their derivatives, an operational matrix for the derivatives is established to reduce the problem to a set of algebraic equations. This new proposed method has the capability of multi-resolution solution with a higher accuracy comparing with other similar methods.

Convolutional neural networks have reached extremely high performances on the Face Recognition task. These models are commonly trained by using high-resolution images and for this reason, their discrimination ability is usually degraded... more

Convolutional neural networks have reached extremely high performances on the Face Recognition task. These models are commonly trained by using high-resolution images and for this reason, their discrimination ability is usually degraded when they are tested against low-resolution images. Thus, Low-Resolution Face Recognition remains an open challenge for deep learning models. Such a scenario is of particular interest for surveillance systems in which it usually happens that a low-resolution probe has to be matched with higher resolution galleries. This task can be especially hard to accomplish since the probe can have resolutions as low as 8, 16 and 24 pixels per side while the typical input of state-of-the-art neural network is 224. In this paper, we described the training campaign we used to fine-tune a ResNet-50 architecture, with Squeeze-and-Excitation blocks, on the tasks of very low and mixed resolutions face recognition. For the training process we used the VGGFace2 dataset and then we tested the performance of the final model on the IJB-B dataset; in particular, we tested the neural network on the 1:1 verification task. In our experiments we considered two different scenarios: 1) probe and gallery with same resolution; 2) probe and gallery with mixed resolutions. Experimental results show that with our approach it is possible to improve upon state-of-the-art models performance on the low and mixed resolution face recognition tasks with a negligible loss at very high resolutions.

HEALPix is a Hierarchical, Equal Area, and iso-Latitude Pixelisation of the sphere designed to support efficiently - local operations on the pixel set, - a hierarchical tree structure for multi-resolution applications, and - the global... more

HEALPix is a Hierarchical, Equal Area, and iso-Latitude Pixelisation of the sphere designed to support efficiently - local operations on the pixel set, - a hierarchical tree structure for multi-resolution applications, and - the global Fast Spherical Harmonic transform. The HEALPix concept and the mathematical software based on it introduced in this primer meet the challenges which future high resolution

The scope of this paper is to analyze and compare three path planning methods for omni-directional robots, which are based on a) the bug algorithm, b) the potential fields algorithm, and c) the A* algorithm for minimum cost path with... more

The scope of this paper is to analyze and compare three path planning methods for omni-directional robots, which are based on a) the bug algorithm, b) the potential fields algorithm, and c) the A* algorithm for minimum cost path with multiresolution grids. The approaches are compared in terms of computational costs and the resulting path lengths. Results obtained indicate that the bug algorithm is a suitable choice for this type of application as its computational cost is lower than that of the other methods. Furthermore, minor modifications of the standard bug algorithm, such as the tangent following modification, allow the path planner to handle well the situations encountered in typical multi-robot environments

Hierarchical binary partitions of multi-dimensional data are investigated as a basis for the construction of effective histograms. Specifically, the impact of adopting lossless compression techniques for representing the histogram on both... more

Hierarchical binary partitions of multi-dimensional data are investigated as a basis for the construction of effective histograms. Specifically, the impact of adopting lossless compression techniques for representing the histogram on both the accuracy and the efficiency of query answering is investigated. Compression is obtained by exploiting the hierarchical partition scheme underlying the histogram, and then introducing further restrictions on the

This paper proposes novel exclusive and continuous approaches to guide the search and the retrieval in fingerprint image databases. Both approaches are useful to perform a coarse level classification of fingerprint images before... more

This paper proposes novel exclusive and continuous approaches to guide the search and the retrieval in fingerprint image databases. Both approaches are useful to perform a coarse level classification of fingerprint images before fingerprint authentication tasks. Our approaches are characterized by:(1) texture image descriptors based on pairs of multi-resolution decomposition methods that encode effectively global and local fingerprint information, with similarity measures used for fingerprint matching purposes, and (2) a ...