Search
Now showing items 1-7 of 7
UAV Swarm Path Planning With Reinforcement Learning for Field Prospecting
(Springer, 2022-03-03)
[Abstract] There has been steady growth in the adoption of Unmanned Aerial Vehicle (UAV) swarms by operators due to their time and cost benefits. However, this kind of system faces an important problem, which is the ...
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal
(Springer Nature, 2019-06-26)
[Abstract]
Sleeping problems have become one of the major diseases all over the world. To tackle this issue, the basic tool used by specialists is the Polysomnogram, which is a collection of different signals recorded ...
Artificial Neuron–Glia Networks Learning Approach Based on Cooperative Coevolution
(World Scientific, 2015-04-06)
[Abstract] Artificial Neuron–Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way ...
EEG Signal Processing with Separable Convolutional Neural Network for Automatic Scoring of Sleeping Stage
(Elsevier, 2020-06-01)
[Abstract]
Nowadays, among the Deep Learning works, there is a tendency to develop networks with millions of
trainable parameters. However, this tendency has two main drawbacks: overfitting and resource consumption due ...
Prediction of Nucleoitide Binding Peptides Using Star Graph Topological Índices
(Elsevier, 2015-08-05)
[Abstract] The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this ...
Population Subset Selection for the Use of a Validation Dataset for Overfitting Control in Genetic Programming
(Taylor & Francis Group, 2019-07-31)
[Abstract] Genetic Programming (GP) is a technique which is able to solve different problems through the evolution of mathematical expressions. However, in order to be applied, its tendency to overfit the data is one of ...
Automatic Assessment of Alzheimer’s Disease Diagnosis Based on Deep Learning Techniques
(Elsevier, 2020-05)
[Abstract]
Early detection is crucial to prevent the progression of Alzheimer’s disease (AD). Thus, specialists can begin preventive treatment as soon as possible. They demand fast and precise assessment in the diagnosis ...
