Search
Now showing items 11-20 of 110
Integrating Iterative Machine Teaching and Active Learning into the Machine Learning Loop
(Elsevier, 2021)
[Abstract] Scholars and practitioners are defining new types of interactions between humans and machine learning algorithms that we can group under the umbrella term of Human-in-the-Loop Machine Learning (HITL-ML). This ...
Segmentation, classification and interpretation of breast cancer medical images using human-in-the-loop machine learning
(Springer, 2024-12-10)
[Abstract]: This paper explores the application of Human-in-the-Loop (HITL) strategies in the training of machine learning models in the medical domain. In this case, a doctor-in-the-loop approach is proposed to leverage ...
Case Study of Anomaly Detection and Quality Control of Energy Efficiency and Hygrothermal Comfort in Buildings
(2019)
[Abstract] The aim of this work is to propose different statistical and machine learning methodologies for identifying
anomalies and control the quality of energy efficiency and hygrothermal comfort in buildings. ...
Adaptive Real-Time Method for Anomaly Detection Using Machine Learning
(MDPI AG, 2020-08-20)
[Abstract]
Anomaly detection is a sub-area of machine learning that deals with the development of methods to distinguish among normal and anomalous data. Due to the frequent use of anomaly-detection systems in monitoring ...
Regression Tree Based Explanation for Anomaly Detection Algorithm
(MDPI AG, 2020-08-18)
[Abstract]
This work presents EADMNC (Explainable Anomaly Detection on Mixed Numerical and Categorical spaces), a novel approach to address explanation using an anomaly detection algorithm, ADMNC, which provides accurate ...
Artificial Intelligence in Pre-University Education: What and How to Teach
(MDPI, 2020-08-26)
[Abstract] The present paper is part of the European Erasmus+ project on educational innovation led by the UDC and entitled “AI+: Developing an Artificial Intelligence Curriculum adapted to European High School”. In this ...
A knowledge model for the development of a framework for hypnogram construction
(Elsevier BV, 2017-02-15)
[Abstract] We describe a proposal of a knowledge model for the development of a framework for hypnogram construction from intelligent analysis of pulmonology and electrophysiological signals. Throughout the twentieth ...
Improving detection of apneic events by learning from examples and treatment of missing data
(I O S Press, 2014)
[Abstract] This paper presents a comparative study over the respiratory pattern classification task involving three missing data imputation techniques, and four different machine learning algorithms. The main goal was to ...
A Machine Learning Solution for Distributed Environments and Edge Computing
(MDPI AG, 2019-08-09)
[Abstract] In a society in which information is a cornerstone the exploding of data is crucial. Thinking of the Internet of Things, we need systems able to learn from massive data and, at the same time, being inexpensive ...
Comparative Analysis of Unsupervised Anomaly Detection Techniques for Heat Detection in Dairy Cattle
(Elsevier, 2025-02-14)
[Abstract] Population growth has increased the demand for meat and dairy products, making livestock, especially cattle, key to meeting this demand. This has led to an increase in herd size, complicating efficient herd ...
