Search results for "Pattern Recognition"
showing 10 items of 2301 documents
Steady-state and tracking analysis of a robust adaptive filter with low computational cost
2007
This paper analyses a new adaptive algorithm that is robust to impulse noise and has a low computational load [E. Soria, J.D. Martin, A.J. Serrano, J. Calpe, and J. Chambers, A new robust adaptive algorithm with low computacional cost, Electron. Lett. 42 (1) (2006) 60-62]. The algorithm is based on two premises: the use of the cost function often used in independent component analysis and a fuzzy modelling of the hyperbolic tangent function. The steady-state error and tracking capability of the algorithm are analysed using conservation methods [A. Sayed, Fundamentals of Adaptive Filtering, Wiley, New York, 2003], thus verifying the correspondence between theory and experimental results.
A new method for linear affine self-calibration of stationary zooming stereo cameras
2012
This paper presents a simple, yet effective, method to recover the affine structure of a scene from a (stereo) pair of stationary zooming cameras. The proposed method solely relies on point correspondences across images and no knowledge about the scene whatsoever is required. Our method exploits implicit properties of the projective camera matrices of zooming cameras and allows to estimate the affine structure of a scene by solving a linear system of equations. The 3D reconstruction results obtained by using our method, on both real and simulated data, have remarkably validated its feasibility.
3-D shape reconstruction in an active stereo vision system using genetic algorithms
2003
Abstract The recovery of 3-D shape information (depth) using stereo vision analysis is one of the major areas in computer vision and has given rise to a great deal of literature in the recent past. The widely known stereo vision methods are the passive stereo vision approaches that use two cameras. Obtaining 3-D information involves the identification of the corresponding 2-D points between left and right images. Most existing methods tackle this matching task from singular points, i.e. finding points in both image planes with more or less the same neighborhood characteristics. One key problem we have to solve is that we are on the first instance unable to know a priori whether a point in t…
Classification of flavonoid compounds by using entropy of information theory
2013
A total of 74 flavonoid compounds are classified into a periodic table by using an algorithm based on the entropy of information theory. Seven features in hierarchical order are used to classify structurally the flavonoids. From these features, the first three mark the group or column, while the last four are used to indicate the row or period in a table of periodic classification. Those flavonoids in the same group and period are suggested to show maximum similarity in properties. Furthermore, those with only the same group will present moderate similarity. In this report, the flavonoid compounds in the table, whose experimental data in bioactivity and antioxidant properties have been prev…
<title>Face modeling: a real-time embedded implementation of a stereovision algorithm</title>
2001
The problem to acquire 3D data of human face can be applied in face recognition, virtual reality, and many other applications. It can be solved using stereovision. This technique consistes in acquiring data in three dimensions from two cameras. The aim is to implement an algorithmic chain which makes it possible to obtain a three-dimensional space from two two-dimensional spaces: two images coming from the two cameras. Several implementations have already been considered. We propose a new simple realtime implementation, based on a multiprocessor approach (FPGA-DSP) allowing to consider an embedded processing. Then we show our method which provides depth map of face, dense and reliable, and …
Realization of an Energetic Hub Based on a High-Performance Dish Stirling Plant
2018
In this work the realization of an energetic hub based on a high-performances dish Stirling system, at the DEIM of the University of Palermo, is presented. The realized system is the first top rated solar thermodynamic plant directly connected to the national electric grid. The connection permits the electricity injection into the grid and allows to access to national renewable energy incentives regime. The system realization was possible thanks to an international cooperation between the University of Palermo and the private company Horizon S.r.l., official partner of Ripasso Energy AB, owner of this technology. Initial data of the plant energy production and the foreseen improvements for …
Hadamard NMR imaging with slice selection
1996
Stochastic NMR imaging is one of the less common NMR imaging techniques. Nevertheless, stochastic rf excitation is characterized by some remarkable features: the rf excitation power is at least two orders of magnitude lower in comparison to conventionally pulsed NMR imaging schemes. Thus, the technique is of interest for imaging of large objects. The systematic noise inherent in images obtained with random noise excitation has been eliminated by using pseudorandom noise together with Hadamard transformation for data evaluation. Data acquisition times are comparable to those of ultrafast imaging techniques. For slice selection, z magnetization is destroyed outside the slice region with speci…
Rapid prototyping for micro-engineering and microfluidic applications: Recycled pmma, a sustainable substrate material
2018
Poly(methylmethacrylate), PMMA, is one of the most commonly used thermoplastics for the manufacture of micromechanical and microfluidic devices, due to its optical transparency, rigid mechanical properties, low cost and good workability in conjunction with its rapid prototyping and mass manufacturing. Recent advances in the rapid-prototyping fields have allowed the production of precise features compatible with microfluidic structures and accelerated the conversion process from bench-side to mass market. For example, to address the need for fast design cycles using material compatible with mass manufacturing, we have developed an ultrafast prototyping technique for the manufacture of multil…
A convolutional neural network for virtual screening of molecular fingerprints
2019
In the last few years, Deep Learning (DL) gained more and more impact on drug design because it allows a huge increase of the prediction accuracy in many stages of such a complex process. In this paper a Virtual Screening (VS) procedure based on Convolutional Neural Networks (CNN) is presented, that is aimed at classifying a set of candidate compounds as regards their biological activity on a particular target protein. The model has been trained on a dataset of active/inactive compounds with respect to the Cyclin-Dependent Kinase 1 (CDK1) a very important protein family, which is heavily involved in regulating the cell cycle. One qualifying point of the proposed approach is the use of molec…
An In-Depth Experimental Comparison of RNTNs and CNNs for Sentence Modeling
2017
The goal of modeling sentences is to accurately represent their meaning for different tasks. A variety of deep learning architectures have been proposed to model sentences, however, little is known about their comparative performance on a common ground, across a variety of datasets, and on the same level of optimization. In this paper, we provide such a novel comparison for two popular architectures, Recursive Neural Tensor Networks (RNTNs) and Convolutional Neural Networks (CNNs). Although RNTNs have been shown to work well in many cases, they require intensive manual labeling due to the vanishing gradient problem. To enable an extensive comparison of the two architectures, this paper empl…