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Classifier Subset Selection to construct multi-classifiers by means of estimation of distribution algorithms
(Elsevier, 2015-01-24)
This paper proposes a novel approach to select the individual classifiers to take part in a Multiple-Classifier System. Individual classifier selection is a key step in the development of multi-classifiers. Several works ...
Blood Cell Revolution: Unveiling 11 Distinct Types with ‘Naturalize’ Augmentation
(MDPI, 2023-12-10)
Artificial intelligence (AI) has emerged as a cutting-edge tool, simultaneously accelerating, securing, and enhancing the diagnosis and treatment of patients. An exemplification of this capability is evident in the analysis ...
dbcsp: User-friendly R package for Distance-Based Common Spatial Patterns
(The R Foundation, 2022-12-20)
Common Spatial Patterns (CSP) is a widely used method to analyse electroencephalography
(EEG) data, concerning the supervised classification of the activity of brain. More generally, it can
be useful to distinguish between ...
New Distance-Based approach for Genome-Wide Association Studies
(IEEE Institute of Electrical and Electronics Engineers Inc., 2022-09-01)
With the rise of genome-wide association studies (GWAS), the analysis of typical GWAS data sets with thousands of single-nucleotide polymorphisms (SNPs) has become crucial in biomedicine research. Here, we propose a new ...
Online Student Authentication and Proctoring System Based on Multimodal Biometrics Technology
(2021-05-11)
Identity veri cation and proctoring of online students are one of the key challenges to online
learning today. Especially for online certi cation and accreditation, the training organizations need to verify
that the ...
Characterizing Permutation-Based Combinatorial Optimization Problems in Fourier Space
(MIT Press, 2023-09-01)
[EN]Comparing combinatorial optimization problems is a difficult task. They are defined using different criteria and terms: weights, flows, distances, etc. In spite of this apparent discrepancy, on many occasions, they ...
COVID-19 Infection Percentage Estimation from Computed Tomography Scans: Results and Insights from the International Per-COVID-19 Challenge
(MDPI, 2024-02-28)
COVID-19 analysis from medical imaging is an important task that has been intensively studied in the last years due to the spread of the COVID-19 pandemic. In fact, medical imaging has often been used as a complementary ...
WebLabel: OpenLABEL-compliant multi-sensor labelling
(Springer Nature, 2024)
Annotated datasets have become crucial for training Machine Learning (ML) models
for developing Autonomous Vehicles (AVs) and their functions. Generating these data-
sets usually involves a complex coordination of ...
Machine Learning First Response to COVID-19: A Systematic Literature Review of Clinical Decision Assistance Approaches during Pandemic Years from 2020 to 2022
(MDPI, 2024-03-07)
Background: The declaration of the COVID-19 pandemic triggered global efforts to control and manage the virus impact. Scientists and researchers have been strongly involved in developing effective strategies that can help ...
Naturalize Revolution: Unprecedented AI-Driven Precision in Skin Cancer Classification Using Deep Learning
(MDPI, 2024-03-01)
Background: In response to the escalating global concerns surrounding skin cancer, this study aims to address the imperative for precise and efficient diagnostic methodologies. Focusing on the intricate task of eight-class ...