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35 results on '"Olvera-López, J. Arturo"'

1. A Comparative Study of Two Algorithms for Computing the Shortest Reducts: MiLIT and MinReduct

Author

Rodríguez-Diez, Vladímir, Martínez-Trinidad, José Fco., Carrasco-Ochoa, J. A., Lazo-Cortés, Manuel S., Olvera-López, J. Arturo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Roman-Rangel, Edgar, editor, Kuri-Morales, Ángel Fernando, editor, Martínez-Trinidad, José Francisco, editor, Carrasco-Ochoa, Jesús Ariel, editor, and Olvera-López, José Arturo, editor

Published
2021
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2. ROIs Segmentation in Facial Images Based on Morphology and Density Concepts

Author

García-Ramírez, Jesús, Olvera-López, J. Arturo, Olmos-Pineda, Ivan, Martín-Ortíz, Manuel, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Carrasco-Ochoa, Jesús Ariel, editor, Martínez-Trinidad, José Francisco, editor, and Olvera-López, José Arturo, editor

Published
2017
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3. Voting Algorithms Model with a Support Sets System by Class

Author

Rodríguez-Salas, Dalia, Lazo-Cortés, Manuel S., Mollineda, Ramón A., Olvera-López, J. Arturo, de la Calleja, Jorge, Benitez, Antonio, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, Series editor, Tanaka, Yuzuru, Series editor, Wahlster, Wolfgang, Series editor, Siekmann, Jörg, Series editor, Gelbukh, Alexander, editor, Espinoza, Félix Castro, editor, and Galicia-Haro, Sofía N., editor

Published
2014
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4. Study of Overlapping Clustering Algorithms Based on Kmeans through FBcubed Metric

Author

Aroche-Villarruel, Argenis A., Carrasco-Ochoa, J. A., Martínez-Trinidad, José Fco., Olvera-López, J. Arturo, Pérez-Suárez, Airel, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Martínez-Trinidad, José Francisco, editor, Carrasco-Ochoa, Jesús Ariel, editor, Olvera-Lopez, José Arturo, editor, Salas-Rodríguez, Joaquín, editor, and Suen, Ching Y., editor

Published
2014
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5. Prototype Selection Via Prototype Relevance

Author

Olvera-López, J. Arturo, Carrasco-Ochoa, J. Ariel, Martínez-Trinidad, J. Fco., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Ruiz-Shulcloper, José, editor, and Kropatsch, Walter G., editor

Published
2008
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7. Mixed Data Object Selection Based on Clustering and Border Objects

Author

Olvera-López, J. Arturo, Martínez-Trinidad, J. Francisco, Carrasco-Ochoa, J. Ariel, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Rueda, Luis, editor, and Mery, Domingo, editor

Published
2007
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8. Edition Schemes Based on BSE

Author

Olvera-López, J. Arturo, Martínez-Trinidad, J. Fco., Carrasco-Ochoa, J. Ariel, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Sanfeliu, Alberto, editor, and Cortés, Manuel Lazo, editor

Published
2005
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16. Motion estimation in vehicular environments based on Bayesian dynamic networks.

Author

Reyes-Cocoletzi, Lauro, Olmos-Pineda, Ivan, Olvera-López, J. Arturo, Pinto, David, Beltrán, Beatriz, and Singh, Vivek

Subjects
BAYESIAN analysis
Abstract

The cornerstone to achieve the development of autonomous ground driving with the lowest possible risk of collision in real traffic environments is the movement estimation obstacle. Predicting trajectories of multiple obstacles in dynamic traffic scenarios is a major challenge, especially when different types of obstacles such as vehicles and pedestrians are involved. According to the issues mentioned, in this work a novel method based on Bayesian dynamic networks is proposed to infer the paths of interest objects (IO). Environmental information is obtained through stereo video, the direction vectors of multiple obstacles are computed and the trajectories with the highest probability of occurrence and the possibility of collision are highlighted. The proposed approach was evaluated using test environments considering different road layouts and multiple obstacles in real-world traffic scenarios. A comparison of the results obtained against the ground truth of the paths taken by each detected IO is performed. According to experimental results, the proposed method obtains a prediction rate of 75% for the change of direction taking into consideration the risk of collision. The importance of the proposal is that it does not obviate the risk of collision in contrast with related work. [ABSTRACT FROM AUTHOR]

Published
2022
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33. Object Selection Based on Clustering and Border Objects.

Author

Kacprzyk, J., Kurzynski, Marek, Puchala, Edward, Wozniak, Michal, Zolnierek, Andrzej, Olvera-López, J. Arturo, Carrasco-Ochoa, J. Ariel, and Martínez-Trinidad, J. Francisco

Abstract

Object selection is an important task for instance-based classifiers since through this process the time in training and classification stages could be reduced. In this work, we propose a new method based on clustering which tries to find border objects that contribute with useful information allowing to the classifier discriminating between classes. An experimental comparison of our method, the CLU method based on clustering, and the DROP methods, is presented. [ABSTRACT FROM AUTHOR]

Published
2008
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34. Mixed Data Object Selection Based on Clustering and Border Objects.

Author

Hutchison, David, Kanade, Takeo, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Pandu Rangan, C., Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Rueda, Luis, Mery, Domingo, Kittler, Josef, Olvera-López, J. Arturo, Martínez-Trinidad, J. Francisco, and Carrasco-Ochoa, J. Ariel

Abstract

In supervised classification, the object selection or instance selection is an important task, mainly for instance-based classifiers since through this process the time in training and classification stages could be reduced. In this work, we propose a new mixed data object selection method based on clustering and border objects. We carried out an experimental comparison between our method and other object selection methods using some mixed data classifiers. [ABSTRACT FROM AUTHOR]

Published
2008
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35. Edition Schemes Based on BSE.

Author

Sanfeliu, Alberto, Cortés, Manuel Lazo, Olvera-López, J. Arturo, Martínez-Trinidad, J. Fco., and Carrasco-Ochoa, J. Ariel

Abstract

Edition is an important and useful task in supervised classification specifically for instance-based classifiers because edition discards from the training set those useless or harmful objects for the classification accuracy and it helps to reduce the size of the original training sample and to increase both the classification speed and accuracy. In this paper, we propose two edition schemes that combine edition methods and sequential search for instance selection. In addition, we present an empirical comparison between these schemes and some other edition methods. [ABSTRACT FROM AUTHOR]

Published
2005
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