Listar DIAN-Artículos, capítulos... por título
Mostrando ítems 99-118 de 188
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Instance selection for multi-label learning based on a scalable evolutionary algorithm
(IEEE, 2021)Multi-label classification has recently attracted greater research interest as a data mining task. Many current ap- plications in data mining address problems having instances that belong to more than one class, which ... -
Integración de la aplicación informática Fonética 2.0 Sistema de composición y generación dinámica de animaciones en la docencia
(Consejo Social de la Universidad de Córdoba, 2010) -
Interactive multi-objective evolutionary optimization of software architectures
(Elsevier, 2018)While working on a software specification, designers usually need to evaluate different architectural alternatives to be sure that quality criteria are met. Even when these quality aspects could be expressed in terms of ... -
Intérprete y depurador gráfico de pseudocódigo español para sistema operativo Linux
(Universidad de Córdoba, Vicerrectorado de Innovación y Calidad Docente, 2004)A pseudo code interpreter in Spanish has been developed in order to the students can learn the basic concepts of programming by means of running their own algorithms. This interpreter works on Linux operative system, which ... -
JCLEC Meets WEKA!
(2014-02-27)WEKA has recently become a very referenced DM tool. In spite of all the functionality it provides, it does not include any framework for the development of evolutionary algorithms. An evolutionary computation framework ... -
JCLEC-MO: A Java suite for solving many-objective optimization engineering problems
(Elsevier, 2019)Although metaheuristics have been widely recognized as efficient techniques to solve real-world optimization problems, implementing them from scratch remains difficult for domain-specific experts without programming skills. ... -
Jewelry Recognition via Encoder-Decoder Models
(IEEE, 2023)Jewelry recognition is a complex task due to the different styles and designs of accessories. Precise descriptions of the various accessories is something that today can only be achieved by experts in the field of ... -
Keypoint descriptor fusion with Dempster-Shafer Theory
(2017)Keypoint matching is the task of accurately nding the location of a scene point in two images. Many keypoint descriptors have been proposed in the literature aiming at providing robustness against scale, translation and ... -
LAIM discretization for multi-label data
(2017)Multi-label learning is a challenging task in data mining which has attracted growing attention in recent years. Despite the fact that many multi-label datasets have continuous features, general algorithms developed specially ... -
Librería para el procesamiento de señales digitales con computadora
(Universidad de Córdoba, Vicerrectorado de Innovación y Calidad Docente, 2004)In this work the basic characteristics of the development and the functionality of a specific software are exposed for the teaching in any matter that includes among their contents the "digital signal processing". The ... -
Local-based k values for multi-label k-nearest neighbors rule
(Elsevier, 2022)Multi-label learning is a growing field in machine learning research. Many applications address instances that simultaneously belong to many categories, which cannot be disregarded if optimal results are desired. Among the ... -
Measuring Spinal Mobility Using an Inertial Measurement Unit System: A Validation Study in Axial Spondyloarthritis
(MDPI, 2020)Portable inertial measurement units (IMUs) are beginning to be used in human motion analysis. These devices can be useful for the evaluation of spinal mobility in individuals with axial spondyloarthritis (axSpA). The ... -
Melanoma Recognition by Fusing Convolutional Blocks and Dynamic Routing between Capsules
(MDPI, 2021)Skin cancer is one of the most common types of cancers in the world, with melanoma being the most lethal form. Automatic melanoma diagnosis from skin images has recently gained attention within the machine learning community, ... -
Memetic Evolutionary Multi-Objective Neural Network Classifier to Predict Graft Survival in Liver Transplant Patients
(2017-02-17)In liver transplantation, matching donor and recipient is a problem that can be solved using machine learning techniques. In this paper we consider a liver transplant dataset obtained from eleven Spanish hospitals, ... -
Memetic Pareto Evolutionary Artificial Neural Networks for the determination of growth limits of Listeria Monocytogenes
(2015-10-08)The main objective of this work is to automatically design neural network models with sigmoidal basis units for classification tasks, so that classifiers are obtained in the most balanced way possible in terms of CCR ... -
MIML library: a Modular and Flexible Library for Multi-instance Multi-label Learning
(Elsevier, 2022)MIML library is a Java software tool to develop, test, and compare classification algorithms for multi-instance multi-label (MIML) learning. The library includes 43 algorithms and provides a specific format and facilities ... -
Minería de datos educativos para la detección de recursos clave
(UCOPress, 2017)Este artículo describe un proyecto de innovación educativa centrado en diseñar y desarrollar un nuevo módulo de Moodle que permita obtener modelos predictivos basados en árboles de decisión a partir de los datos de uso ... -
Mixing body-parts model for 2D human pose estimation in stereo videos
(Institution of Engineering and Technology, 2017)This study targets 2D articulated human pose estimation (i.e. localisation of body limbs) in stereo videos. Although in recent years depth-based devices (e.g. Microsoft Kinect) have gained popularity, as they perform very ... -
ML-k’sNN: Label Dependent k Values for Multi-Label k-Nearest Neighbor Rule
(MDPI, 2023)Multi-label classification as a data mining task has recently attracted increasing interest from researchers. Many current data mining applications address problems with instances that belong to more than one category. ... -
Modeling and predicting students’ engagement behaviors using mixture Markov models
(Springer, 2022)Students’ engagements reflect their level of involvement in an ongoing learning processwhich can be estimated through their interactions with a computer-based learning or assessment system. A pre-requirement for stimulating ...