Estas son las colecciones en las que puede catalogar la producción investigadora del departamento Lenguajes y Ciencias de la Computación. Si considera que ninguna de estas se ajusta a su material pida una nueva colección en la sección de sugerencias.

Colecciones en esta comunidad

Envíos recientes

  • Development of artificial neural network-based object detection algorithms for low-cost hardware devices 

    de Benito Picazo, Jose Jesús (UMA Editorial, 2021-12-01)
    The human brain is the most complex, powerful and versatile learning machine ever known. Consequently, many scientists of various disciplines are fascinated by its structures and information processing methods. Due to the ...
  • Modelos de predicción de crisis financieras internacionales con técnicas de aprendizaje automático: aplicaciones a la reputación país 

    Alaminos Aguilera, David (UMA Editorial, 2021-11-10)
    El presente estudio ha escogido tres de los tipos más importantes de crisis tratadas en las finanzas internacionales: la crisis de deuda soberana, la crisis de divisas y la crisis sistémica bancaria. Por tanto, se trata ...
  • Energy-efficient Deployment of IoT Applications in Edge-based Infrastructures: A Software Product Line Approach 

    Cañete Valverde, Ángel Jesús; Fuentes-Fernández, Lidia; Amor-Pinilla, Maria Mercedes (2021-09)
    In order to lower latency and reduce energy consumption, Edge Computing proposes offloading some computation intensive tasks usually performed in the Cloud onto nearby devices in the frontier/Edge of the access networks. ...
  • Hierarchical Color Quantization with a Neural Gas Model Based on Bregman Divergences 

    Palomo, Esteban J.; Benito Picazo, Jesús; Domínguez-Merino, Enrique; López-Rubio, Ezequiel; Ortega-Zamorano, Francisco (Springer, 2021-09)
    In this paper, a new color quantization method based on a self-organized artificial neural network called the Growing Hierarchical Bregman Neural Gas (GHBNG) is proposed. This neural network is based on Bregman divergences, ...
  • Peer assessments in Engineering: A pilot project 

    Thurnhofer-Hemsi, Karl; Molina-Cabello, Miguel A.; Palomo, Esteban J.; López-Rubio, Ezequiel; Domínguez, Enrique (2021)
    The evaluation methods employed in a course are the most important point for the students, above any other learning aspect. For teachers, this task is arduous when the number of students is high. Traditional evaluation ...
  • Longitudinal study of the learning styles evolution in Engineering degrees 

    Molina-Cabello, Miguel A.; Thurnhofer-Hemsi, Karl; Domínguez, Enrique; López-Rubio, Ezequiel; Palomo, Esteban J. (2021)
    A learning style describes what are the predominant skills for learning tasks. In the context of university education, knowing the learning styles of the students constitutes a great opportunity to improve both teaching ...
  • Skin lesion classification by ensembles of deep convolutional networks and regularly spaced shifting 

    Thurnhofer Hemsi, Karl; López Rubio, Ezequiel; Domínguez, Enrique; Elizondo, David A. (2021)
    Skin lesions are caused due to multiple factors, like allergies, infections, exposition to the sun, etc. These skin diseases have become a challenge in medical diagnosis due to visual similarities, where image classification ...
  • Ensemble ellipse fitting by spatial median consensus 

    Thurnhofer Hemsi, Karl; López Rubio, Ezequiel; Blázquez Parra, Elidia Beatriz; Ladrón de Guevara Muñoz, María Carmen; De Cózar Macías, Óscar David (2021)
    Ellipses are among the most frequently used geometric models in visual pattern recognition and digital image analysis. This work aims to combine the outputs of an ensemble of ellipse fitting methods, so that the deleterious ...
  • Kafka-ML: Connecting the data stream with ML/AI frameworks 

    Martín Fernández, Cristian; Langendoerfer, Peter; Soltani Zarrin, Pouya; Díaz-Rodríguez, Manuel; Rubio-Muñoz, Bartolome (Elsevier, 2022-01-01)
    Machine Learning (ML) and Artificial Intelligence (AI) depend on data sources to train, improve, and make predictions through their algorithms. With the digital revolution and current paradigms like the Internet of Things, ...
  • Enhanced transfer learning model by image shifting on a square lattice for skin lesion malignancy assessment 

    Molina Cabello, Miguel A.; Thurnhofer Hemsi, Karl; Maza Quiroga, Rosa María; Domínguez, Enrique; López-Rubio, Ezequiel; [et al.] (2021)
    Skin cancer is one of the most prevalent diseases among people. Physicians have a challenge every time they have to determine whether a diseased skin is benign or malign. There exist clinical diagnosis methods (such as ...
  • Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning 

    Calderón-Ramírez, Saúl; Murillo-Hernández, Diego; Rojas-Salazar, Kevin; Calvo-Valverde, Luis-Alexander; Yang, Shengxiang; [et al.] (2021-07)
    Computer aided diagnosis for mammogram images have seen positive results through the usage of deep learning architectures. However, limited sample sizes for the target datasets might prevent the usage of a deep learning ...
  • Histopathological image analysis for breast cancer diagnosis by ensembles of convolutional neural networks and genetic algorithms 

    Molina Cabello, Miguel A.; Rodríguez Rodríguez, José Antonio; Thurnhofer Hemsi, Karl; López-Rubio, Ezequiel (2021-07)
    One of the most invasive cancer types which affect women is breast cancer. Unfortunately, it exhibits a high mortality rate. Automated histopathological image analysis can help to diagnose the disease. Therefore, computer ...
  • Detection of tumor morphology mentions in clinical reports in spanish using transformers 

    López-García, Guillermo; Jerez-Aragonés, José Manuel; Ribelles-Entrena, Nuria; Alba-Conejo, Emilio; Veredas-Navarro, Francisco Javier (Springer, 2021)
    The aim of this study is to systematically examine the performance of transformer-based models for the detection of tumor morphology mentions in clinical documents in Spanish. For this purpose, we analyzed 3 transformer ...
  • An open source framework based on Kafka-ML for Distributed DNN inference over the Cloud-to-Things continuum 

    Torres, Daniel R.; Martín, Cristian; Díaz, Manuel; Rubio-Muñoz, Bartolome (Elsevier, 2021-06-16)
    The current dependency of Artificial Intelligence (AI) systems on Cloud computing implies higher transmission latency and bandwidth consumption. Moreover, it challenges the real-time monitoring of physical objects, e.g., ...
  • Unified Management of Applications on Heterogeneous Clouds 

    Carrasco Mora, Jose Manuel (UMA Editorial, 2021-06-18)
    La diversidad con la que los proveedores cloud ofrecen sus servicios, definiendo sus propias interfaces y acuerdos de calidad y de uso, dificulta la portabilidad y la interoperabilidad entre proveedores, lo que incurre en ...
  • Self-Organized Maps 

    Díaz-Ramos, Antonio (UMA Editorial, 2021-05-26)
    Los mapas auto-organizados o redes de Kohonen (SOM por sus siglas en inglés, self-organizing map) fueron introducidos por el profesor finlandés Teuvo Kalevi Kohonen en los años 80. Un mapa auto-organizado es una herramienta ...
  • Robust computational intelligence techniques for visual information processing 

    Thurnhofer Hemsi, Karl Khader (UMA Editorial, 2021-05-12)
    This Ph.D. thesis is about image processing by computational intelligence techniques. Firstly, a general overview of this book is carried out, where the motivation, the hypothesis, the objectives, and the methodology ...
  • Deep Neuroevolution: Smart City Applications 

    Camero Unzueta, Andres (UMA Editorial, 2021-05-05)
    El interés por desarrollar redes neuronales artificiales ha resurgido de la mano del Aprendizaje Profundo. En términos simples, el aprendizaje profundo consiste en diseñar y entrenar una red neuronal de gran complejidad y ...
  • Processing Structured Data Streams 

    Barquero Moreno, Gala (UMA Editorial, 2021)
    A large amount of data is daily generated from different sources such as social networks, recommendation systems or geolocation systems. Moreover, this information tends to grow exponentially every year. Companies have ...
  • Reputación Corporativa: Modelos para el Análisis y Valoración de la Dimensión Financiera de Entes Públicos y Privados 

    Fernández Miguélez, Sergio Manuel (UMA Editorial, 2021-05-05)
    Los activos intangibles representan actualmente un importante componente estratégico de las organizaciones y están orientados a la gestión del conocimiento y del capital intelectual. Uno de los principales activos intangibles ...

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