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Listar por palabra clave "Machine learning"

Mostrando ítems 1-20 de 575

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A Cloud-Based Framework for Machine Learning Workloads and Applications

Lopez Garcia, Alvaro; Marco De Lucas, Jesús; Antonacci, Marica; Zu Castell, Wolfgang; David, Mario; Hardt, Marcus; Lloret Iglesias, Lara; Moltó, Germán; Plociennik, Marcin; Tran, Viet; Alic, Andrei Stefan; Caballer Fernández, Miguel; Campos Plasencia, Isabel; Costantini, Alessandro; Dlugolinsky, Stefan (Institute of Electrical and Electronics Engineers, 2020-01-06)

[EN] In this paper we propose a distributed architecture to provide machine learning practitioners with a set of tools and cloud services that cover the whole machine learning development cycle: ranging from the models ...
A comparative study of Neural Machine Translation frameworks for the automatic translation of open data resources

Iranzo Sánchez, Javier (Universitat Politècnica de València, 2018-09-11)

[EN] Machine Translation (MT) is one of the most active areas in Artificial Intelligence, particularly in Pattern Recognition. MT has recently received a great deal of attention by key technology players such as Google, ...
A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry

Lorente-Leyva, Leandro L.; Alemany Díaz, María Del Mar; Peluffo-Ordóñez, Diego H.; Herrera-Granda, Israel D. (Springer-Verlag, 2021-01-07)

[EN] This document presents a comparison of demand forecasting methods, with the aim of improving demand forecasting and with it, the production planning system of Ecuadorian textile industry. These industries present ...
A comparison of machine learning classifiers for leak detection and isolation in urban networks

Carreño-Alvarado, Elizabeth P.; Reynoso-Meza, Gilberto; Montalvo, Idel; Izquierdo Sebastián, Joaquín (International Center for Numerical Methods in Engineering (CIMNE), 2017-07-05)

[EN] Leak detection and isolation (LDI) is a problem of interest for water management companies and their technical staff. Main reasons for this are that early detection of leakages can reduce dramatically (1) water ...
A comparison of machine learning models for the detection of metastatic tissue in axillary lymph nodes

Abad Martínez, Javier (Universitat Politècnica de València, 2020-07-30)

[EN] Breast cancer is currently the leading cause of death due to cancer in women, after lung cancer. For its diagnosis and staging, detection of metastatic tissue in axillary lymph nodes is occasionally used, since lymphatic ...
A comprehensive survey of multi-view video summarization

Hussain, Tanveer; Muhammad, Khan; Ding, Weiping; Lloret, Jaime; Baik, Sung Wook; de Albuquerque, Victor Hugo C. (Elsevier, 2021-01)

[EN] There has been an exponential growth in the amount of visual data on a daily basis acquired from single or multi-view surveillance camera networks. This massive amount of data requires efficient mechanisms such as ...
A dataset of attributes from papers of a machine learning conference

Vallejo-Huanga, Diego; Morillo, Paulina; Ferri Ramírez, César (Elsevier, 2019-06)

[EN] In this work, we present a dataset which provides information on the scientific program of a set conferences of Machine Learning. Data were extracted from the IEEE Xplore Digital Library and the official web site of ...
A Digital Twin of a Water Distribution System by Using Graph Convolutional Networks for Pump Speed-Based State Estimation

Bonilla, Carlos A.; Znafei, Ariele; Brentan, Bruno; Montalvo, Idel; Izquierdo Sebastián, Joaquín (MDPI AG, 2022-02)

[EN] Water distribution system monitoring is currently carried out using advanced real-time control technologies to achieve a higher operational efficiency. Data analysis techniques can be implemented for condition estimation, ...
A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time

Martínez Martínez, Francisco; Rupérez Moreno, María José; Martínez-Sober, M.; Solves Llorens, Juan Antonio; Lorente, D.; Serrano-Lopez, A.J.; Martinez-Sanchis, Sandra; Monserrat, C.; Martin-Guerrero, J.D. (Elsevier, 2017-11-01)

[EN] This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed ...
A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning

Lorente, D.; Martínez-Martínez, F.; Rupérez Moreno, María José; Lago, M. A.; Martínez-Sober, M.; Escandell-Montero, P.; Martínez-Martínez, J. M.; Martínez-Sanchis, S.; Serrano-López, A.J.; Monserrat, C.; Martín-Guerrero, J.D. (Elsevier, 2017-04-01)

Progress in biomechanical modelling of human soft tissue is the basis for the development of new clinical applications capable of improving the diagnosis and treatment of some diseases (e.g. cancer), as well as the surgical ...
A hierarchical model to electricity load forecasting

Díaz-Alejo León, Stéphane (Universitat Politècnica de València, 2021-09-07)

[EN] Load forecasting models have drawn attention over the last decade, due to the fact that are of great help to the modernization of the power grid, and consequently, to the environment. In particular, models that use ...
A machine learning approach to Czech readability

Williams, Peter; Reynolds, Robert (Editorial Universitat Politècnica de València, 2024-02-12)

[EN] We present a new corpus of Czech texts labeled for second-language readability, and show results of experiments to train machine-learning classifiers to automatically label new texts according to reading level. We ...
A Machine Learning SDN-Enabled Big Data Model for IoMT System

Haseeb, Khalid; Ahmad, Irshad; Iqbal Awan, Israr; Lloret, Jaime; Bosch Roig, Ignacio (MDPI AG, 2021-09)

[EN] In recent times, health applications have been gaining rapid popularity in smart cities using the Internet of Medical Things (IoMT). Many real-time solutions are giving benefits to both patients and professionals for ...
A multinational study on artificial intelligence adoption: Clinical implementers' perspectives

MARCO RUIZ, LUIS; Tejedor Hernández, Miguel Angel; Ngo, Phuong Dinh; Makhlysheva, Alexandra; Svenning, Therese Olsen; Dyb, Kari; Chomutare, Taridzo; Fernández Llatas, Carlos; Muñoz-Gama, Jorge; Tayefi, Maryam (Elsevier, 2024-04)

[EN] Background: Despite substantial progress in AI research for healthcare, translating research achievements to AI systems in clinical settings is challenging and, in many cases, unsatisfactory. As a result, many AI ...
A neural network approach for chatter prediction in turning

Cherukuri, Harish; Pérez Bernabeu, Elena; Sellés, M.A.; Schmitz, Tony L. (Elsevier, 2019)

[EN] Machining processes, including turning, are a critical capability for discrete part production. One limitation to high material removal rates and reduced cost in these processes is chatter, or unstable spindle speed-chip ...
A review of the use of machine learning techniques in eco-innovation research

Diez Martinez, Ines; Peiró Signés, Ángel (Editorial Universitat Politècnica de València, 2023-01-10)

[EN] Machine learning is a powerful tool used across research all over the world. Machine learning algorithms are a form of artificial intelligence that allows more accurate predictions of causal conditions of all kinds, ...
A robust multimedia traffic SDN-Based management system using patterns and models of QoE estimation with BRNN

Canovas Solbes, Alejandro; REGO MAÑEZ, ALBERT; Romero Martínez, José Oscar; Lloret, Jaime (Elsevier, 2020-01-15)

[EN] Nowadays, network infrastructures such as Software Defined Networks (SDN) achieve a huge computational power. This allows to add a high processing on the network nodes. In this paper, a multimedia traffic management ...
A serverless gateway for event-driven machine learning inference in multiple clouds

Naranjo-Delgado, Diana María; Risco, Sebastián; Moltó, Germán; Blanquer Espert, Ignacio (John Wiley & Sons, 2023-08-15)

[EN] Serverless computing and, in particular, the functions as a service model has become a convincing paradigm for the development and implementation of highly scalable applications in the cloud. This is due to the ...
A Smart Architecture for Diabetic Patient Monitoring Using Machine Learning Algorithms

Rghioui, Amine; Lloret, Jaime; Sendra, Sandra; Oumnad, Abdelmajid (MDPI AG, 2020-09-19)

[EN] Continuous monitoring of diabetic patients improves their quality of life. The use of multiple technologies such as the Internet of Things (IoT), embedded systems, communication technologies, artificial intelligence, ...
A Smart Glucose Monitoring System for Diabetic Patient

Rghioui, Amine; Lloret, Jaime; Harane, Mohamed; Oumnad,Abdelmajid (MDPI AG, 2020-04-22)

[EN] Diabetic patients need ongoing surveillance, but this involves high costs for the government and family. The combined use of information and communication technologies (ICTs), artificial intelligence and smart devices ...