Listar por autor "0000-0002-3400-9279"
Mostrando ítems 1-20 de 23
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3D Convolutional Neural Network to Enhance Small-Animal Positron Emission Tomography Images in the Sinogram Domain
Vergara Villegas, Osslan Osiris (Springer, 2022-06-11)In this work, we propose a three dimensional (3D) convolutional neural network (CNN) to enhance sinograms acquired from a small-animal positron emission tomography (PET) scanner. The network consists of three convolutional ... -
A methodology for character recognition and revision of the linear equations solving procedure
Vergara Villegas, Osslan Osiris (2023-01-01)Linear equations are valuable for real-world modeling phenomena involving at least one variable. However, verifying if the procedure followed by a human for solving a linear equation was done correctly is still a complicated ... -
Aplicación para la Manipulación y Visualización de Imágenes de Tomografía por Emisión de Positrones (PET)
Cornejo Monroy, Delfino; Ochoa Domínguez, Humberto; 194448; Núñez Sánchez, Aliuska (Academia Journals, 2021-05-14)La tomografía por emisión de positrones (PET) es una técnica médica para el diagnóstico de enfermedades como el cáncer, enfermedades cardíacas y trastornos cerebrales. Debido al alto costo de tomógrafos PET y la necesidad ... -
Aplicación TIC para el Control y Administración de Redes y Agrupaciones Ciudadanas (ARAC)
Gutierrez Casas, Efren David (2019-11-19)La aplicación TIC para el Control y Administración de Redes y Agrupaciones Ciudadanas (ARAC) permite de manera fácil y eficiente conformar la base de datos de los simpatizantes, voluntarios o miembros de una red o agrupación ... -
Auto-adaptive Multilayer Perceptron for Univariate Time Series Classification
Cruz Sanchez, Vianey Guadalupe; Ochoa Domínguez, Humberto; García, Vicente; Vergara Villegas, Osslan Osiris; 171515; Arias del Campo, Felipe (2021-05-19)Time Series Classification (TSC) is an intricate problem that has encountered applications in various science fields. Accordingly, many researchers have presented interesting proposals to tackle the TSC problem. ... -
Auto-regularized Gradients of Adaptive Interpolation for MRI Super-Resolution
Morera Delfin, Leandro (2018-10-10)In this paper, a method for adaptive pure interpolation (PI) of magnetic resonance imaging (MRI) in the frequency domain, with gradient auto-regularization, is proposed. The input image is transformed into the frequency ... -
Comparison of Deep Learning Architectures in Classification of Microcalcifications Clusters in Digital Mammograms
Ochoa Domínguez, Humberto; Vergara Villegas, Osslan Osiris; Cruz Sanchez, Vianey Guadalupe; 216618; Luna Lozoya, Ricardo Salvador; Sossa, Juan Humberto (Springer, 2023-06-09)Microcalcifications clusters (MCCs) are relevant breast cancer indirect evidence and early detection can prevent death. In this paper, we carry out a comparison of the deep learning architectures (DL) InceptionV3, ... -
Comparison of Reconstruction Strategies of Compressive Sensing Applied to Ultrasound Images
TOLEDO, ERICK (SPRINGER, 2018-10-18)Ultrasound medical images are important for medical diagnose. The method allows the real-time visualization of organs of the body and it is not invasive. In this study, a comparison of reconstruction greedy search ... -
Denoising of Ultrasound Medical Images Using the DM6437 High-Performance Digital Media Processor
Martínez Medrano, Gerardo Adrián (Springer International Publishing AG, 2018-04-29)Medical ultrasound images are inherently contaminated by a multiplicative noise called speckle. The noise reduces the resolution and contrast, decreasing the capability of the visual evaluation of the image, and sometimes ... -
Dictionary-based super resolution for positron emission tomography images
Rodríguez Hernández, Leandro José (2019-09-11)In this paper, a strategy to increase the resolution of positron emission tomography (PET) images, using a previously trained high resolution dictionary for the sinograms is proposed. The low resolution input sinogram is ... -
Discrete Cosine Transform, Second Edition
Ochoa Dominguez, Humberto De Jesus (CRC-Press, 2019-05-07) -
Dissimilarity-Based Linear Models for Corporate Bankruptcy Prediction
García, Vicente (2019-03-01)Bankruptcy prediction has acquired great relevance for financial institutions due to the complexity of global economies and the growing number of corporate failures, especially since the world financial crisis of 2008. In ... -
Driving Maximal Frequency Content and Natural Slopes Sharpening for Image Amplification with High Scale Factor
Leandro Morera, Delfin (2018-05-05)In this paper, a method for adaptive Pure Interpolation (PI) in the frequency domain, with gradient auto-regularization, is proposed. he input image is transformed into the frequency domain and convolved with the Fourier ... -
Estudio comparativo de algoritmos de súper resolución de una sola imagen basados en aprendizaje profundo
Ochoa Domínguez, Humberto (2020-12-12)El problema de la súper resolución comprende un conjunto de métodos de procesamiento digital de imágenes; su objetivo es incrementar la resolución de las imágenes para mejorar su calidad visual. En años recientes, con el ... -
High Amplification Scales Handling Frequency Content and Novel Gradient Sharpening Procedures
Morera Delfin, Leandro (2018-07-30)In this paper, a method for adaptive pure interpolation (PI) in the frequency domain, with gradient auto-regularization, is proposed. The input image is transformed into the frequency domain and convolved with the Fourier ... -
International Conference on Digital Science (DSIC 2018)
Toledo Gómez, Erick (Springer Cham, 2018-10-19)Ultrasound medical images are important for medical diagnose. The method allows the real-time visualization of organs of the body and it is not invasive. In this study, a comparison of reconstruction greedy search methods, ... -
Mexican traffic sign detection and classification using deep learning
Mendoza, Carlos; Vergara Villegas, Osslan Osiris; Ochoa Domínguez, Humberto; Cruz Sanchez, Vianey Guadalupe; Castruita, Rubén (2022-04-25)En este trabajo tiene se propone una metodología para la detección y clasificación de señales de tránsito mexicanas utilizando aprendizaje profundo. La metodología consiste en la creación de un nuevo conjunto de datos de ... -
Overview of Super-resolution Techniques
Morera Delfín, Leandro (Springer, Cham, 2018-04-28)In the last three decades, multi-frame and single-frame super-resolution and reconstruction techniques have been receiving increasing attention because of the large number of applications that many areas have found when ... -
Radial Basis Function Neural Network for the Evaluation of Image Color Quality Shown on Liquid Crystal Displays
Vergara Villegas, Osslan Osiris; Cruz Sanchez, Vianey Guadalupe; Ochoa Domínguez, Humberto; Nandayapa, Manuel; Arias del Campo, Felipe; 171515 (2021-02-01)The color quality of an image shown on a liquid crystal display (LCD) can be measured with a spectroradiometer; however, this instrument is expensive, work under controlled illumination conditions with an artificial source ... -
Residual 3D convolutional neural network to enhance sinograms from small-animal positron emission tomography images
Ochoa Domínguez, Humberto; Vergara Villegas, Osslan Osiris; Cruz Sanchez, Vianey Guadalupe; Polanco Gonzalez, Javier; 194726; Rodríguez, Leandro José; Sossa, Juan Humberto (2023-05-05)Positron emission tomography (PET) has been widely used in nuclear medicine to diagnose cancer. PET images suffer from degradation because of the scanner’s physical limitations, the radiotracer’s reduced dose, and the ...