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Mostrando ítems 1-10 de 18
Artículo
A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation
(Elsevier, 2017)
Breast cancer is the most common cause of cancer death in women. Today, post-transcriptional protein products of the genes involved in breast cancer can be identified by immunohistochemistry. However, this method has ...
Ponencia
Análisis Big Data para la Respuesta a la Demanda en el Mercado Eléctrico
(Asociación Española para la Inteligencia Artificial (AEPIA), 2018)
El modelo de negocio tradicional de las compañías energéticas está cambiando los últimos años. La introducción de los contadores inteligentes ha conll evado un aumento exponencial del volumen de datos disponibles, y su ...
Artículo
Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities
(MDPI, 2018)
New technologies such as sensor networks have been incorporated into the management of buildings for organizations and cities. Sensor networks have led to an exponential increase in the volume of data available in recent ...
Artículo
Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance
(Elsevier, 2020)
Breast cancer is the most frequent cancer in women and the second most frequent overall after lung cancer. Although the 5-year survival rate of breast cancer is relatively high, recurrence is also common which often ...
Artículo
Statistically Representative Metrology of Nanoparticles via Unsupervised Machine Learning of TEM Images
(MDPI, 2021)
The morphology of nanoparticles governs their properties for a range of important applica tions. Thus, the ability to statistically correlate this key particle performance parameter is paramount in achieving accurate ...
Artículo
Object detection using depth completion and camera-LiDAR fusion for autonomous driving
(IOS Press, 2022)
Autonomous vehicles are equipped with complimentary sensors to perceive the environment accurately. Deep learning models have proven to be the most effective approach for computer vision problems. Therefore, in autonomous ...
Artículo
External clustering validity index based on chi-squared statistical test
(Elsevier, 2019)
Clustering is one of the most commonly used techniques in data mining. Its main goal is to group objects into clusters so that each group contains objects that are more similar to each other than to objects in other ...
Artículo
An approach to validity indices for clustering techniques in Big Data
(Springer, 2018)
Clustering analysis is one of the most used Machine Learning techniques to discover groups among data objects. Some clustering methods require the number of clus ters into which the data is going to be partitioned. There ...
Ponencia
Indexes to Find the Optimal Number of Clusters in a Hierarchical Clustering
(Springer, 2019)
Clustering analysis is one of the most commonly used techniques for uncovering patterns in data mining. Most clustering methods require establishing the number of clusters beforehand. However, due to the size of the data ...
Tesis Doctoral
Predicción de series temporales en streaming mediante Deep Learning
(2022-06-27)
Esta tesis, presentada como un compendio de artículos de investigación, aborda la predicción de series temporales en un entorno de streaming mediante técnicas de deep learning. En primer lugar, se aporta un innovador ...