Search results for " categorization"

Gabor filtering for feature extraction on complex images: application to defect detection on semiconductors

2006

AbstractThis paper is an extension of previous work on the image segmentation of electronic structures on patterned wafers to improve the defect detection process on optical inspection tools. Die-to-die wafer inspection is based upon the comparison of the same area on two neighbourhood dies. The dissimilarities between the images are a result of defects in this area of one of the dies. The noise level can vary from one structure to the other, within the same image. Therefore, segmentation is needed to create a mask and apply an optimal threshold in each region. Contrast variation on the texture can affect the response of the parameters used for the segmentation. This paper shows a method of…

Mammographic images segmentation based on chaotic map clustering algorithm

2013

Background: This work investigates the applicability of a novel clustering approach to the segmentation of mammographic digital images. The chaotic map clustering algorithm is used to group together similar subsets of image pixels resulting in a medically meaningful partition of the mammography. Methods: The image is divided into pixels subsets characterized by a set of conveniently chosen features and each of the corresponding points in the feature space is associated to a map. A mutual coupling strength between the maps depending on the associated distance between feature space points is subsequently introduced. On the system of maps, the simulated evolution through chaotic dynamics leads…

Energy performance of architectural heritage: characteristics of the historic buildings in Palermo

2015

The current researches on the energy and environmental improvement of historic architecture aim to develop strategies respectful of its aesthetic and material features. This requires a deep knowledge of the characters strictly connected to a local context. This paper focuses on the historic architecture of Palermo and analyses, among its features, those which particularly influence its energy and environmental performance. For this purpose the building typologies introduced by the urban regulations can be useful for a categorization on the basis of the most recent European researches.

A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics

2006

We propose a new distributed image segmentation algorithm structured as a multiagent system composed of a set of segmentation agents and a coordinator agent. Starting from its own initial image, each segmentation agent performs the iterated conditional modes method, known as ICM, in applications based on Markov random fields, to obtain a sub-optimal segmented image. The coordinator agent diversifies the initial images using the genetic crossover and mutation operators along with the extremal optimization local search. This combination increases the efficiency of our algorithm and ensures its convergence to an optimal segmentation as it is shown through some experimental results.

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization With Medical Applications

2019

Medical applications challenge today's text categorization techniques by demanding both high accuracy and ease-of-interpretation. Although deep learning has provided a leap ahead in accuracy, this leap comes at the sacrifice of interpretability. To address this accuracy-interpretability challenge, we here introduce, for the first time, a text categorization approach that leverages the recently introduced Tsetlin Machine. In all brevity, we represent the terms of a text as propositional variables. From these, we capture categories using simple propositional formulae, such as: if "rash" and "reaction" and "penicillin" then Allergy. The Tsetlin Machine learns these formulae from a labelled tex…

A genetic algorithm for image segmentation

2002

The paper describes a new algorithm for image segmentation. It is based on a genetic approach that allow us to consider the segmentation problem as a global optimization problem (GOP). For this purpose, a fitness function, based on the similarity between images, has been defined. The similarity is a function of both the intensity and the spatial position of pixels. Preliminary results, obtained using real images, show a good performance of the segmentation algorithm.

Gravitational weighted fuzzy c-means with application on multispectral image segmentation

2014

This paper presents a novel clustering approach based on the classic Fuzzy c-means algorithm. The approach is inspired from the concept of interaction between objects in physics. Each data point is regarded as a particle. A specific weight is associated with each data particle depending on its interaction with other particles. This interaction is induced by attraction forces between pairs of particles and the escape velocity from other particles. Classification experiments using two data sets from UCI repository demonstrate the outperformance of the proposed approach over other clustering algorithms. In addition, results demonstrate the effectiveness of the proposed scheme for segmentation …

Il miglioramento energetico nel recupero degli edifici storici. Applicazione al patrimonio architettonico palermitano

L'architettura storica può assumere un ruolo rilevante nel raggiungimento degli obiettivi europei di efficienza energetica per il settore edile, obiettivi che, tuttavia, devono essere compatibili con la conservazione del patrimonio storico e del suo valore culturale. A tal fine è necessario far riferimento ai caratteri specifici dell'architettura storica e alla sua dimensione locale. La presente tesi, sulla base di tale assunto, esamina le prestazioni energetiche degli edifici storici e il loro potenziale miglioramento, concentrandosi sul patrimonio architettonico di Palermo, caso di studio significativo per l'area mediterranea. La ricerca, condotta con riferimento sia alla scala urbana sia…

Image Segmentation by Deep Community Detection Approach

2017

International audience; To address the problem of segmenting an image into homogeneous communities this paper proposes an efficient algorithm to detect deep communities in the image by maximizing at each stage a new centrality measure, called the local Fiedler vector centrality (LFVC). This measure is associated with the sensitivity of algebraic connectivity to node removals. We show that a greedy node removal strategy, based on iterative maximization of LFVC, has bounded performance loss relative to the optimal, but intractable, combinatorial batch removal strategy. A remarkable feature of this method is the ability to segments the image automatically into homogeneous regions by maximizing…

Revisión de la categoría «adverbio» en español

2009

Among all word classes, the adverb is the worst defined and studied grammatical category. All grammarians accept that this category includes very heterogeneous elements, which come from very different origins and have very different functions. There is thus an urgent need to review this grammatical category. With this work, I intend to find an answer to the following questions: How the grammatical theory on the adverb has been developed? Which have been the mistakes of the grammatical tradition by producing a theory on the adverb? What should we actually understand by an adverb? How can we order, in a proper and reasonable way, the elements which are presently grouped in the so called «adve…