Titlebook: Computational Science and Its Applications – ICCSA 2020; 20th International C Osvaldo Gervasi,Beniamino Murgante,Yeliz Karaca Conference pr

Biofeedback

Bouquet

A Dynamic Latent Variable Model for Monitoring the Santa Maria del Fiore Dome Behavioria del Fiore, in Florence. First cracks in the Dome appeared at the end of the 15th century and nowadays they are present in all the Dome’s webs, although with an heterogenous distribution. A monitoring system has been installed in the Dome since 1955 to monitor the behavior of the cracks; today, it

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Comparing Statistical and Machine Learning Imputation Techniques in Breast Cancer Classificationmpares the impacts of two statistical and two machine learning imputation techniques when classifying breast cancer patients, using several evaluation metrics. Mean, Expectation-Maximization (EM), Support Vector Regression (SVR) and K-Nearest Neighbor (KNN) were applied to impute 18% of missing data

细胞学

Exploring Algorithmic Fairness in Deep Speaker Verifications voice to a unique digital identity representation for verification. Despite the increasing accuracy achieved so far, it still remains under-explored how the decisions made by such systems may be influenced by the inherent characteristics of the individual under consideration. In this paper, we inv

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septicemia

A Comparative Analysis of State-of-the-Art Recommendation Techniques in the Movie Domainnline sites selling products and services provide users with RSs that can assist them in their online experience. In recent years, therefore, we have witnessed an impressive series of proposals for novel recommendation techniques that claim to ensure significative improvements compared to classic te

Osmosis

Automated Machine Learning: Prospects and Challengesspiration have recently shown promising results in automatically designing neural network architectures. However, apart from back-propagation, only a few applications of other learning techniques are used for these purposes. The back-propagation process takes advantage of specific optimization techn

埋伏

left-ventricle

frenzy

Detection of Thyroid Nodules Through Neural Networks and Processing of Echographic Imagesposals are presented for the identification of thyroid nodules in ultrasound images, using convolutional neural networks. For the network training, 400 images obtained from a medical center and stored in a database have been used. Free access software (Python and TensorFlow) has been used as part of