Search results for "Pattern"
showing 10 items of 4203 documents
Salient Pixels and Dimensionality Reduction for Display of Multi/Hyperspectral Images
2012
International audience; Dimensionality Reduction (DR) of spectral images is a common approach to different purposes such as visualization, noise removal or compression. Most methods such as PCA or band selection use either the entire population of pixels or a uniformly sampled subset in order to compute a projection matrix. By doing so, spatial information is not accurately handled and all the objects contained in the scene are given the same emphasis. Nonetheless, it is possible to focus the DR on the separation of specific Objects of Interest (OoI), simply by neglecting all the others. In PCA for instance, instead of using the variance of the scene in each spectral channel, we show that i…
Delineation of Malignant Skin Tumors by Hyperspectral Imaging
2018
This chapter outlines a new non-invasive method for delineation of skin lesions such as lentigo maligna and lentigo maligna melanoma. The method is based on the analysis of hyperspectral (HS) images taken in vivo before surgical excision of the lesions. For this, characteristic features of the spectral signatures of diseased pixels and healthy pixels are extracted, which combine the intensities in a few selected wavebands with the coefficients of the wavelet frame transforms of the spectral curves. To reduce dimensionality and to reveal the internal structure of the datasets, the diffusion maps (DM) technique is applied. The averaged Nearest Neighbor and the Classification and Regression Tr…
Rapid and Nondestructive Determination of Egg Freshness Category and Marked Date of Lay using Spectral Fingerprint
2020
The potential of nondestructive prediction of egg freshness based on near-infrared (NIR) spectra fingerprints would be beneficial to quality control officers and consumers alike. In this study, handheld NIR spectrometer in the range of 740 nm to 1070 nm and chemometrics were used to simultaneously determine egg freshness based on marked date of lay for eggs stored under cold and ambient conditions. The spectra acquired from the eggs were preprocessed using multiplicative scatter correction and principal component analysis (MSC-PCA). Linear discriminant analysis (LDA) was used to build identification model to predict the category of freshness, while partial least square regression (PLS-R) wa…
Analysis of pattern recognition by man using detection experiments.
1981
This paper addresses the problem of analyzing biological pattern recognition systems. As no complete analysis is possible due to limited observability, the theoretical part of the paper examines some principles of construction for recognition systems. The relations between measurable and characteristic variables of these systems are described. The results of the study are: 1. Human recognition systems can always be described by a model consisting of an analyzer (FA) and a linear classifier. 2. The linearity of the classifier places no limits on the universal validity of the model. The principle of organization of such a system may be put into effect in many different ways. 3. The analyzer f…
Improved SOM Learning using Simulated Annealing
2007
Self-Organizing Map (SOM) algorithm has been extensively used for analysis and classification problems. For this kind of problems, datasets become more and more large and it is necessary to speed up the SOM learning. In this paper we present an application of the Simulated Annealing (SA) procedure to the SOM learning algorithm. The goal of the algorithm is to obtain fast learning and better performance in terms of matching of input data and regularity of the obtained map. An advantage of the proposed technique is that it preserves the simplicity of the basic algorithm. Several tests, carried out on different large datasets, demonstrate the effectiveness of the proposed algorithm in comparis…
Alignment-Free Sequence Comparison over Hadoop for Computational Biology
2015
Sequence comparison i.e., The assessment of how similar two biological sequences are to each other, is a fundamental and routine task in Computational Biology and Bioinformatics. Classically, alignment methods are the de facto standard for such an assessment. In fact, considerable research efforts for the development of efficient algorithms, both on classic and parallel architectures, has been carried out in the past 50 years. Due to the growing amount of sequence data being produced, a new class of methods has emerged: Alignment-free methods. Research in this ares has become very intense in the past few years, stimulated by the advent of Next Generation Sequencing technologies, since those…
Magnetic resonance imaging of the siliceous skeleton of the demosponge Lubomirskia baicalensis
2005
The skeletal elements (spicules) of the demosponge Lubomirskia baicalensis were analyzed; they are composed of amorphous, non-crystalline silica, and contain in a central axial canal the axial filament which consists of the enzyme silicatein. The axial filament, that orients the spicule in its longitudinal axis exists also in the center of the spines which decorate the spicule. During growth of the sponge, new serially arranged modules which are formed from longitudinally arranged spicule bundles are added at the tip of the branches. X-ray analysis revealed that these serial modules are separated from each other by septate zones (annuli). We describe that the longitudinal bundles of spicule…
FPGA implementation of Spiking Neural Networks supported by a Software Design Environment
2011
Abstract This paper is focused on the creation of Spiking Neural Networks (SNN) in hardware due to their advantages for certain problem solving and their similarity to biological neural system. One of the main uses of this neural structure is pattern classification. The chosen model for the spiking neuron is the Spike Response Model (SRM). For SNN design and implementation, a software application has been developed to provide easy creation, simulation and automatic generation of the hardware model. VHDL was used for the hardware model. This paper describes the functionality of SNN and the design procedure followed to obtain a working neural system in both software and hardware. Designed VHD…
Self-organization and nanostructural control in thin film heterojunctions.
2013
In spite of more than two-decades of studies of molecular self-assembly, the achievement of low cost, easy-to-implement and multi-parameter bottom-up approaches to address the supramolecular morphology in three-dimensional (3D) systems is still missing. In the particular case of molecular thin films, the 3D nanoscale morphology and function are crucial for both fundamental and applied research. Here we show how it is possible to tune the 3D film structure (domain size, branching, etc.) of thin film heterojunctions with nanoscale accuracy together with the modulation of their optoelectronic properties by employing an easy two-step approach. At first we prepared multi-planar heterojunctions w…
Salient Spin Images: A Descriptor for 3D Object Recognition
2018
In the last decades a wide range of algorithms have been devoted to recognize 3D free-from objects under real conditions such as occlusions, clutters, rotation, scale and translation. Spin image is one of these algorithms known to be robust to rotation, translation, occlusions up to 70% and clutters up to 60%, but still suffer from scaling, resolution changes and it is time consuming. In this paper we present a novel approach based on spin images, called salient spin images (SSI). This method enhances spin images algorithm based on its limits. Particularly, it decreases significantly the complexity of the algorithm using DoG detector, it shows a higher performance due to the relevant locali…