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Found 7 papers, 1 papers with code
Machine Learning in management of precautionary closures caused by lipophilic biotoxins
The main risk to mussel farming is harmful algal blooms (HABs), which pose a risk to human consumption.
Ensemble of Convolution Neural Networks on Heterogeneous Signals for Sleep Stage Scoring
Over the years, several approaches have tried to tackle the problem of performing an automatic scoring of the sleeping stages.
Automatic Assessment of Alzheimer's Disease Diagnosis Based on Deep Learning Techniques
There are two main conclusions to be drawn from this work: first, the damages related to AD and its stages can be distinguished in sagittal MRI and, second, the results obtained using DL models with sagittal MRIs are similar to the state-of-the-art, which uses the horizontal-plane MRI.
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal
This process is carried out manually, which can be highly time-consuming and very prone to annotation errors.
Classical Music Prediction and Composition by means of Variational Autoencoders
However, results show that the system is able to return accurate representations and predictions in unseen data.
Classification of Two-channel Signals by Means of Genetic Programming
Traditionally, signal classification is a process in which previous knowledge of the signals is needed.
NCBO Ontology Recommender 2.0: An Enhanced Approach for Biomedical Ontology Recommendation
To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms.
