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Pollutant concentrations and Meteorological data classification by Neural Networks
A. Vega-Corona;J. M. Barrón-Adame;O. G. Ibarra-Manzano;M. G. Cortina-Januchs;J. Quintanilla-Dominguez;D. Andina
World Automation Congress 2012
Year: 2012 | Conference Paper |
This paper present an environmental contingency forecasting tool based on Neural Networks (NN). Forecasting tool analyzes every hour and daily Sulphur Dioxide (SO2) concentrations and Meteorological data time series. Pollutant concentrations and meteorological variables are self-organized applying a Self-organizing Map (SOM) NN in different classes. Classes are used in training phase of a General ...Show More
ANN and Fuzzy c-Means applied to environmental pollution prediction
M.G. Cortina-Januchs;J. Quintanilla-Domínguez;D. Andina;Antonio Vega-Corona
World Automation Congress 2012
Year: 2012 | Conference Paper |
Salamanca, situated in center of Mexico is among the cities which suffer most from the air pollution in Mexico. The vehicular park and the industry, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Sulphur Dioxide (SO2). In this work, a Multilayer Perceptron Neural Network has been used to make the prediction of an hour ahead of polluta...Show More
Unsupervised method to classify PM10 pollutant concentrations
A. Vega-Corona;J.M. Barrón-Adame;J.A. Herrera-Delgado;J. Quintanilla-Domínguez;M.G. Cortina-Januchs;D. Andina
World Automation Congress 2012
Year: 2012 | Conference Paper |
In this paper a method based mainly on Data Fusion and Artificial Neural Networks to classify one of the most important pollutants such as Particulate Matter less than 10 micrometer in diameter (PM10) concentrations is proposed. The main objective is to classify in two pollution levels (Non-Contingency and Contingency) the pollutant concentration. Pollutant concentrations and meteorological variab...Show More
Prediction of PM10 concentrations using Fuzzy c-Means and ANN
M.G. Cortina-Januchs;J. Quintanilla-Domínguez;D. Andina;Antonio Vega-Corona
IECON 2011 - 37th Annual Conference of the IEEE Industrial Electronics Society
Year: 2011 | Conference Paper |
Salamanca has been considered among the most polluted cities in Mexico. The vehicular park, the industry and the emissions produced by agriculture, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Particulate Matter less than 10 μg/m3 in diameter (PM10). In this work, a Multilayer Perceptron Neural Network has been used to make the pred...Show More
Feature selection using Sequential Forward Selection and classification applying Artificial Metaplasticity Neural Network
A. Marcano-Cedeño;J. Quintanilla-Domínguez;M. G. Cortina-Januchs;D. Andina
IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society
Year: 2010 | Conference Paper |
Cited by: Papers (125)
The feature selection has been widely used to reduce the data dimensionality. Data reduction improve the classification performance, the approximation function, and pattern recognition systems in terms of speed, accuracy and simplicity. A strategy to reduce the number of features in local search are the sequential search algorithms. In this work is presented a feature selection method based on Seq...Show More
Color image segmentation by partitional clustering algorithms
B. Ojeda-Magaña;R. Ruelas;J. Quintanilla-Domínguez;D. Andina
IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society
Year: 2010 | Conference Paper |
Cited by: Papers (7)
This paper presents the results of some partitional clustering algorithms applied to the segmentation of color images in the RGB space. As more information is involved in the algorithm, and the distance measure is more flexible, the better the results. The selected algorithms for this work are the K-means, the FCM, the GK-B, and the GKPFCM. The GKPFCM gives the better results when all the algorith...Show More
Microcalcification detection applying artificial neural networks and mathematical morphology in digital mammograms
J. Quintanilla-Dominguez;M.G. Cortina-Januchs;B. Ojeda-magaña;Aleksandar Jevtić;A. Vega-Corona;D. Andina
Breast cancer is one of the leading causes to women mortality in the world and early detection is an important means to reduce the mortality rate. The presence of microcalcifications clusters has been considered as a very important indicator of malignant types of breast cancer and its detection is important to prevent and treat the disease. This paper presents an alternative and effective approach...Show More
Air pollution analysis with a PFCM clustering algorithm applied in a real database of Salamanca (Mexico)
B. Ojeda-Magaña;M. G. Cortina-Januchs;J. M. Barrón-Adame;J. Quintanilla-Domínguez;W. Hernandez;A. Vega-Corona;R. Ruelas;D. Andina
2010 IEEE International Conference on Industrial Technology
Year: 2010 | Conference Paper |
Cited by: Papers (3)
Over the last ten years, Salamanca has been considered among the most polluted cities in México. Nowadays, there is an Automatic Environmental Monitoring Network (AEMN) which measures air pollutants (Sulphur Dioxide (SO2), Particular Matter (PM10), Ozone (O3), etc.), as well as environmental variables (wind speed, wind direction, temperature, and relative humidity), and it takes a sample of the va...Show More
Wood defects classification using Artificial Metaplasticity neural network
2009 35th Annual Conference of IEEE Industrial Electronics
Year: 2009 | Conference Paper |
Cited by: Papers (15)
Artificial Metaplasticity (AMP) is a novel Artificial Neural Network (ANN) training algorithm inspired in biological metaplasticity property of neurons and Shannon's information theory. During training phase, the AMP training algorithm gives more relevance to the less frequent patterns and subtracts relevance to the frequent ones, achieving a much more efficient training, while at least maintainin...Show More
Combination of nonlinear filters and ANN for detection of microcalcifications in digitized mammography
J. Quintanilla-Domínguez;M. G. Cortina-Januchs;Aleksandar Jevtić;D. Andina;J. M. Barrón-Adame;A. Vega-Corona
2009 IEEE International Conference on Systems, Man and Cybernetics
Year: 2009 | Conference Paper |
Cited by: Papers (1)
Breast cancer is one of the leading causes to women mortality in the world. Cluster of Microcalcifications (MCCs) in mammograms can be an important early sign of breast cancer, the detection is important to prevent and treat the disease. In this paper, we present a novel method for the detection of MCCs in mammograms which consists of image enhancement by histogram adaptive equalization technique,...Show More
Edge detection using ant colony search algorithm and multiscale contrast enhancement
Aleksandar Jevtić;Joel Quintanilla-Dominguez;M. G. Cortina-Januchs;Diego Andina
2009 IEEE International Conference on Systems, Man and Cybernetics
Year: 2009 | Conference Paper |
Cited by: Papers (19)
In this paper, Ant Colony System (ACS) algorithm is applied for edge detection in grayscale images. The novelty of the proposed method is to extract a set of images from the original grayscale image using Multiscale Adaptive Gain for image contrast enhancement and then apply the ACS algorithm to detect the edges on each of the extracted images. The resulting set of images represents the pheromone ...Show More
Feature extraction using coordinate logic filters and Artificial Neural Networks
J. Quintanilla-Dominguez;M. Sanchez-Garcia;M. Gozalez-Romo;A. Vega-Corona;D. Andina
2009 7th IEEE International Conference on Industrial Informatics
Year: 2009 | Conference Paper |
Cited by: Papers (2)
This paper presents a novel feature extraction method using the combination of the Coordinate Logic Filters (CLF) and Artificial Neural Networks (ANN) applied to 2D signals (Images). The method consists of image enhancement by histogram adaptive equalization technique, features extraction by modifying gray levels applying a nonlinear adaptive transformation function and edge detection by Coordinat...Show More
Images sub-segmentation with the PFCM clustering algorithm
B. Ojeda-Magana;J. Quintanilla-Dominguez;R. Ruelas;D. Andina
2009 7th IEEE International Conference on Industrial Informatics
Year: 2009 | Conference Paper |
Cited by: Papers (13)
In this work we propose a method for sub-segmentation of images using the PFCM clustering algorithm. The sub-segmentation consists of finding, within the clusters found using the segmentation process, those data less representative, or atypical data, belonging to the clusters. These data represent, in many cases, the zones of interest during image analysis. Two different examples are used in order...Show More
Contextual and Non-Contextual Features Extraction and a Selection Method for Microcalcifications Detection
Antonio Vega-Corona;Moises Sanchez-Garcia;Mario Gonzalez-Romo;Joel Quintanilla-Dominguez;J. Miguel Barron-Adame
In this paper a method to extract and build patterns to model microcalcifications from digitized mammography is presented. The proposed method consist in a combination of two steps, in the first one, a feature extraction method is applied using multiscale wavelet image processing, and is combined with a Self Organizing Neural Network to solve the segmentation image problem. In the second one, a fe...Show More
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