Papers by Dr. Iván E Villalón Turrubiates
Exploring Machine Learning Algorithms-Aid Diagnosis for Chronic Kidney Disease
Aggregation of the Regularization and Dynamic Filtration Techniques for Enhanced Remote Sensing Imaging with Intelligent Resource Management
... Outstanding Citizen - City of Salamanca Mexico, 2008; MS Scholarship 165660 - CONACYT Mexico ... more ... Outstanding Citizen - City of Salamanca Mexico, 2008; MS Scholarship 165660 - CONACYT Mexico 2001-2003; Ph.D. Scholarship 165660 - CONACYT Mexico 2005-2007; Marquis Who's Who in the World - 2007; Best Evaluated Professor - TECMilenio University 2010. ...
Desarrollo de Modelos Adaptivos para el Procesamiento Digital de Señales Multiespectrales de Percepción Remota y su Implementación como Software de Alto Desempeño
In Mexico, the incorporation of deaf people into education has been lacking since only 14% of the... more In Mexico, the incorporation of deaf people into education has been lacking since only 14% of the deaf population in the age group between 3 and 29 years access education with the support of a hearing aid. Additionally, those who have been incorporated frequently face inappropriate educational strategies which poorly develop the use of Mexican Sign Language (MSL) and therefore academical success and opportunities for insertion in the workplace are difficult. This research explores a novel mexican sign language lexicon video dataset containing the dynamical gestures most frequently used by MSL. Each gesture consists of a set of different versions of videos under uncontrolled conditions. MX-ITESO-100 data set is composed of a lexicon of 100 gestures and 5,000 videos from three participants with different grammatical elements. Additionally, the data set is evaluated in a two-step neural network model with an accuracy greater than 99%. and thus serves as a benchmark for future training ...
Mathematics
The capability analysis of a process against requirements is often an instrument of change. The t... more The capability analysis of a process against requirements is often an instrument of change. The traditional and fuzzy process capability approaches are the most useful statistical techniques for determining the intrinsic spread of a controlled process for establishing realistic specifications and use for comparative processes. In the industry, the traditional approach is the most commonly used instrument to assess the impact of continuous improvement projects. However, these methods used to evaluate process capability indices could give misleading results because the dataset employed corresponds to the final product/service measures. This paper reviews an alternative procedure to assess the fuzzy process capability indices based on the statistical methodology involved in the modeling and design of experiments. Firstly, a model with reasonable accuracy is developed using a neural network approach. This model is embedded in a graphic user interface (GUI). Using the GUI, an experimenta...
Alternative method for determining basis weight in papermaking by using an interactive soft sensor based on an artificial neural network model
Nordic Pulp & Paper Research Journal
Currently, there are two procedures to determine the basis weight in papermaking processes: the m... more Currently, there are two procedures to determine the basis weight in papermaking processes: the measurements made by the quality control laboratory or the measurements made by the quality control system. This research presents an alternative to estimating basis weight-based artificial neural network (ANN) modeling. The NN architecture was constructed by trial and error, obtaining the best results using two hidden layers with 48 and 12 neurons, respectively, in addition to the input and output layers. Mean absolute error and mean absolute percentage error was used for the loss and metric functions, respectively. Python was used in the training, validation, and testing process. The results indicate that the model can reasonably determine the basis weight given the independent variables analyzed here. The R 2 {R^{2}} reached by the model was 94 %, and MAE was 12.40 grams/m2. Using the same dataset, the fine tree regression model showed an R 2 {R^{2}} of 99 % and an MAE of 3.35 grams/m2...
This study consider the problem of high-resolution imaging of the remote sensing (RS) environment... more This study consider the problem of high-resolution imaging of the remote sensing (RS) environment formalized in terms of a nonlinear ill- posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the wavefield scattered from an extended remotely sensed scene (referred to as the scene image). However, the remote sensing techniques for reconstructive imaging in many RS application areas are relatively unacceptable for being implemented in a (near) real time implementation. In this work, we address a new aggregated descriptive-regularization (DR) method and the Hardware/Software (HW/SW) co-design for the SSP reconstruction from the uncertain speckle-corrupted measurement data in a computationally efficient parallel fashion that meets the (near) real time image processing requirements. The hardware design is performed via efficient systolic arrays (SAs). Finally, the efficiency both in resolution enhancement and in computational complexity reductio...
The paper suggest a novel approach to the problem of high-resolution array radar/SAR imaging as a... more The paper suggest a novel approach to the problem of high-resolution array radar/SAR imaging as an ill-conditioned inverse spatial spectrum pattern (SSP) estimation problem with model uncertainties. We explain the theory recently developed by the authors of this presentation that addresses a new fused Bayesian-regularization paradigm for radar/SAR image formation/reconstruction. We show how this theory leads to new adaptive and robustified computational methods that enable one to derive efficient and consistent estimates of the SSP via unifying the Bayesian minimum risk estimation strategy with the ME randomized a priori image model and other projection-type regularization constraints imposed on the solution. We detail such fused Bayesian-regularization (FBR) paradigm and analyze some efficient numerical schemes for computational implementation of the relevant FBR-based methods. Also, we present the results of extended simulation study of the family of the radar image (RI) formation...
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 1, 2017
The classification procedure to identify remote sensing signatures from a particular geographical... more The classification procedure to identify remote sensing signatures from a particular geographical region can be achieved using an accurate identification model that is based on multispectral data and uses pixel statistics for the class description. This methodology is referred to as the Multispectral Identification Model. This paper presents this particular methodology applied to large remote sensing datasets (multispectral images obtained from the SPOT-5 satellite sensors) with the objective to perform environmental and land use analysis for regions within Mexico, taking advantage of high-performance computing techniques to improve the processing time and computational load. The results obtained uses real multispectral scenes (highresolution optical images) to probe the efficiency of the classification technique.
Journal of Intelligent & Fuzzy Systems, 2018
This work highlights how to transform information from invoice documents to semantic models, as a... more This work highlights how to transform information from invoice documents to semantic models, as an implementation of ontology modeling. The migration from printed paper to digital documents in the Mexican Government Offices in the last few years has brought significant opportunities for the usage of information technologies and applications. However, when changing digital document information into knowledge, there are still many gaps to be filled. This work proposes a solution to some issues regarding ontology modeling, specifically when mapping a document that follows some XML schema to an ontology under the OWL standard. The main contribution of this work is to provide new interpretations of the XML terms in the context of OWL, so that the XML Schema Definition (XSD) structures can be mapped into more complex OWL structures. A software tool developed to test and validate the information extraction strategies proposed is presented here.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016
Desarrollo de Modelos Adaptivos para el Procesamiento Digital de Señales Multiespectrales de Percepción Remota y su Implementación como Software de Alto Desempeño
2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015
A novel algorithm to generate a tridimensional reconstruction of an object using a series of imag... more A novel algorithm to generate a tridimensional reconstruction of an object using a series of images obtained with sensors within low-cost cameras is proposed. As a matter of particular study, this paper present the methodology employed to set an array of sensors to extract the necessary information from a particular group of acquired images surrounding the sample, the processing schema for its interpretation and its mapping, in order to approximate a tridimensional model with the use of real data. The simulation results can verify the efficiency of the proposed approach, showing an application where it could be a useful tool for decision support or resource management.
2006 International Conference on Image Processing, 2006
In this paper, the problem of estimating from a finite set of measurements of the radar remotely ... more In this paper, the problem of estimating from a finite set of measurements of the radar remotely sensed complex data signals, the power spatial spectrum pattern (SSP) of the wavefield sources distributed in the environment is cast in the framework of Bayesian minimum risk (MR) paradigm unified with the experiment design (ED) regularization technique. The fused MR-ED regularization of the ill-posed nonlinear inverse problem of the SSP reconstruction is performed via incorporating into the MR estimation strategy the projection-regularization ED constraints. The simulation examples are incorporated to illustrate the efficiency of the proposed unified MR-ED technique.
IEEE Geoscience and Remote Sensing Magazine, 2014
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2007
The robust numerical technique for high-resolution reconstructive imaging and scene analysis is d... more The robust numerical technique for high-resolution reconstructive imaging and scene analysis is developed as required for enhanced remote sensing with large scale sensor array radar/synthetic aperture radar. The problemoriented modification of the previously proposed fused Bayesian-regularization (FBR) enhanced radar imaging method is performed to enable it to reconstruct remote sensing signatures (RSS) of interest alleviating problem illposeness due to system-level and model-level uncertainties. We report some simulation results of hydrological RSS reconstruction from enhanced real-world environmental images indicative of the efficiency of the developed method.
1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.
We address a new approach to the problem of improvement of the quality of scene images obtained w... more We address a new approach to the problem of improvement of the quality of scene images obtained with several sensing systems as required for remote sensing imagery, in which case we propose to exploit the idea of robust regularization aggregated with the neural network (NN) based computational implementation of the multisensor fusion tasks. Such a specific aggregated robust regularization problem is stated and solved to reach the aims of system fusion with a proper control of the NN's design parameters (synaptic weights and bias inputs viewed as corresponding system-level and model-level degrees of freedom) which influence the overall reconstruction performances.
1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.
In this paper, the problem of estimating from a finite set of measurements of the radar remotely ... more In this paper, the problem of estimating from a finite set of measurements of the radar remotely sensed complex data signals, the power spatial spectrum pattern (SSP) of the wavefield sources distributed in the environment is cast in the framework of Bayesian minimum risk (MR) paradigm unified with the experiment design (ED) regularization technique. The fused MR-ED regularization of the illposed nonlinear inverse problem of the SSP reconstruction is performed via incorporating into the MR estimation strategy the projection-regularization ED constraints. The simulation examples are incorporated to illustrate the efficiency of the proposed unified MR-ED technique.
2010 IEEE International Geoscience and Remote Sensing Symposium, 2010
Much of human history can be traced through the impacts of human actions upon the environment. Th... more Much of human history can be traced through the impacts of human actions upon the environment. The use of remote sensing technology offers the archeologist the opportunity to detect these impacts which are often invisible to the naked eye. The extraction of remote sensing signatures from a particular geographical region allows the generation of geophysical signature maps; this can be achieved using an accurate and recently developed multispectral image classification approach based on pixel statistics for the class description, which is referred to as the Weighted Pixel Statistics method. This paper presents the prospective study of the effectiveness that this approach provides for supervised segmentation and classification of sensed archaeological signatures for land use analysis. The results obtained with this study uses real multispectral scenes obtained with remote sensing techniques (high-resolution synthetic aperture radar) to probe the efficiency of the classification technique.
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Papers by Dr. Iván E Villalón Turrubiates