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Now showing items 11-20 of 23
A Python implementation of the Snakes and Ladders for solving the Hamiltonian cycle problem using a graphical interface
(2021-10-08)
[EN] Given a graph, the Hamiltonian cycle problem (HCP) consists of finding a cycle in a given graph that passes through every single vertex exactly once, or determining that this cannot be achieved. This problem has several ...
Music composition and interpretation using transformer networks
(2020-12-04)
This work presents the development of a deep learning model capable of generating and completing musical compositions automatically through generative algorithms of machine learning from a language modeling approach.
...
Solving combinatorial optimization problems using quantum computing: a case study for the QAP
(2020-12-04)
Quantum computing is one of the most researched areas in computer science and withone of the greatest future prospects thanks to the new discoveries and methodologies thatcan provide approaches of a different kind to tackle ...
Quantum extreme learning machine for classification tasks
(2022-10-19)
Quantum Computing is one of the most researched areas in computer science and physics, however, current quantum computers are influenced by unwanted noise from environmental factors. Quantum Extreme Learning Machine (QELM) ...
User friendly image denoising based on deep learning
(2022-10-19)
Idioma: Ingles
Dado el gran rendimiento de los métodos basados en aprendizaje profundo en visión por computador y, en concreto, en reducción de ruido en imágenes y vídeos, se propone crear una herramienta web que permita ...
Analysis of the influence of sex in diagnostic classification of Parkinson's disease based on non-motor manifestations by means of machine learning methods
(2022-10-19)
Parkinson’s disease (PD) is the second most common neurodegenerative disorder, after
Alzheimer’s disease. In the early stages of the disease, when motor symptoms have not
yet manifested themselves, the accuracy of making ...
Deep neural networks and data augmentationfor semantic labelling in a dialogue corpus
(2020-12-04)
El presente proyecto estudia y aplica técnicas de Deep Neural Networks y Data Augmentation para el etiquetado semántico en un corpus de diálogo, todo ello en el ámbito del Sentiment Analysis.
El objetivo principal es ...
Easy-to-use deep learning based super-resolution in microscopy images
(2021-10-08)
[ES]El TFG trata de la investigación de una red neuronal reciente de super-resolución así como su implementación en un notebook fácil de usar dirigido a gente no experta en programación.
Time-renormalization for the search of periodic solutions to the three-body problem
(2021-10-08)
Researchers Antoñana et al. developed a technique for global time-renormalization of the
gravitational N-body problem. In their paper, it is speculated that it may be useful for
finding periodic orbits, but they do not ...