Displaying similar documents to “Improving surface defect detection for quality assessment of car body panels.”

Localization and fuzzy classification of manufacturing defects in sheets of glass.

Luis Junco Navascués, Luciano Sánchez (1998)

Mathware and Soft Computing

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Artificial Vision Systems are commonly used in industrial applications. The low cost of the equipment facilitates the development of new products. In this paper we describe the use of an artificial vision system in one of the phases of a quality control process related to automotive industries: the windshield manufacturing. We intend to localize and classify the defects that were originated while manufacturing the glass that forms the windshield. We will show that a fuzzy classifier,...

Rough set-based dimensionality reduction for supervised and unsupervised learning

Qiang Shen, Alexios Chouchoulas (2001)

International Journal of Applied Mathematics and Computer Science

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The curse of dimensionality is a damning factor for numerous potentially powerful machine learning techniques. Widely approved and otherwise elegant methodologies used for a number of different tasks ranging from classification to function approximation exhibit relatively high computational complexity with respect to dimensionality. This limits severely the applicability of such techniques to real world problems. Rough set theory is a formal methodology that can be employed to reduce...

Fuzzy approach for data association in image tracking.

Julio García, José Manuel Molina, Juan Alberto Besada, Javier I. Portillo (2003)

Mathware and Soft Computing

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A fuzzy system has been developed to ponder update decisions both for the trajectories and shapes estimated for targets. It is embedded in an A-SMGCS Surveillance function for airport surface, based on video data processing, in charge of the automatic detection, identification and tracking of all interesting targets (aircraft and relevant ground vehicles). The tracking system captures a sequence of images, preprocesses them to extract the moving regions (blobs), and associates the blobs...

Neuro-rough-fuzzy approach for regression modelling from missing data

Krzysztof Simiński (2012)

International Journal of Applied Mathematics and Computer Science

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Real life data sets often suffer from missing data. The neuro-rough-fuzzy systems proposed hitherto often cannot handle such situations. The paper presents a neuro-fuzzy system for data sets with missing values. The proposed solution is a complete neuro-fuzzy system. The system creates a rough fuzzy model from presented data (both full and with missing values) and is able to elaborate the answer for full and missing data examples. The paper also describes the dedicated clustering algorithm....

Evolutionary algorithms and fuzzy sets for discovering temporal rules

Stephen G. Matthews, Mario A. Gongora, Adrian A. Hopgood (2013)

International Journal of Applied Mathematics and Computer Science

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A novel method is presented for mining fuzzy association rules that have a temporal pattern. Our proposed method contributes towards discovering temporal patterns that could otherwise be lost from defining the membership functions before the mining process. The novelty of this research lies in exploring the composition of fuzzy and temporal association rules, and using a multi-objective evolutionary algorithm combined with iterative rule learning to mine many rules. Temporal patterns...

New aspects on extraction of fuzzy rules using neural networks.

José Manuel Benítez, Armando Blanco, Miguel Delgado, Ignacio Requena (1998)

Mathware and Soft Computing

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In previous works, we have presented two methodologies to obtain fuzzy rules in order to describe the behaviour of a system. We have used Artificial Neural Netorks (ANN) with the Backpropagation algorithm, and a set of examples of the system. In this work, some modifications which allow to improve the results, by means of an adaptation or refinement of the variable labels in each rule, or the extraction of local rules using distributed ANN, are showed. An interesting application on the...

DFIS: A novel data filling approach for an incomplete soft set

Hongwu Qin, Xiuqin Ma, Tutut Herawan, Jasni Mohamad Zain (2012)

International Journal of Applied Mathematics and Computer Science

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The research on incomplete soft sets is an integral part of the research on soft sets and has been initiated recently. However, the existing approach for dealing with incomplete soft sets is only applicable to decision making and has low forecasting accuracy. In order to solve these problems, in this paper we propose a novel data filling approach for incomplete soft sets. The missing data are filled in terms of the association degree between the parameters when a stronger association...

Learning imprecise semantic concepts from image databases.

Daniel Sánchez, Jesús Chamorro-Martínez (2002)

Mathware and Soft Computing

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In this paper we introduce a model to represent high-level semantic concepts that can be perceived in images. The concepts are learned and represented by means of a set of association rules that relate the presence of perceptual features to the fulfillment of a concept for a set of images. Since both the set of images where a perceptual feature appears and the set of images fulfilling a given concept are fuzzy, we use in fact fuzzy association rules for the learning model. The concepts...