E-LIB Suche - Ergebnisse für: Charte, David

1

Reducing Data Complexity Using Autoencoders With Class-Info..:

Charte, David ; Charte, Francisco ; Herrera, Francisco
IEEE Transactions on Pattern Analysis and Machine Intelligence. 44 (2022) 12 - p. 9549-9560 , 2022

Link: https://doi.org/10.1109/..

2

A tutorial on the segmentation of metallographic images: Ta..:

Luengo, Julián ; Moreno, Raúl ; Sevillano, Iván...
Information Fusion. 78 (2022) - p. 232-253 , 2022

Link: https://doi.org/10.1016/..

3

Slicer: Feature Learning for Class Separability with Least-..:

, In: Lecture Notes in Computer Science; Hybrid Artificial Intelligent Systems,

Charte, David ; Sevillano-García, Iván ; Lucena-González, María Jesús... - p. 305-315 , 2021

Link: https://doi.org/10.1007/..

4

Revisiting data complexity metrics based on morphology for ..:

Pascual-Triana, José Daniel ; Charte, David ; Andrés Arroyo, Marta..
Knowledge and Information Systems. 63 (2021) 7 - p. 1961-1989 , 2021

Link: https://doi.org/10.1007/..

5

Artificial intelligence within the interplay between natura..:

Górriz, Juan M. ; Ramírez, Javier ; Ortíz, Andrés...
Neurocomputing. 410 (2020) - p. 237-270 , 2020

Link: https://doi.org/10.1016/..

6

An analysis on the use of autoencoders for representation l..:

Charte, David ; Charte, Francisco ; del Jesus, María J..
Neurocomputing. 404 (2020) - p. 93-107 , 2020

Link: https://doi.org/10.1016/..

7

A Showcase of the Use of Autoencoders in Feature Learning A..:

, In: From Bioinspired Systems and Biomedical Applications to Machine Learning; Lecture Notes in Computer Science,

Charte, David ; Charte, Francisco ; del Jesus, María J.. - p. 412-421 , 2019

Link: https://doi.org/10.1007/..

8

Ruta: Implementations of neural autoencoders in R:

Charte, David ; Herrera, Francisco ; Charte, Francisco
Knowledge-Based Systems. 174 (2019) - p. 4-8 , 2019

Link: https://doi.org/10.1016/..

9

A practical tutorial on autoencoders for nonlinear feature ..:

Charte, David ; Charte, Francisco ; García, Salvador..
Information Fusion. 44 (2018) - p. 78-96 , 2018

Link: https://doi.org/10.1016/..

10

A snapshot on nonstandard supervised learning problems: tax..:

Charte, David ; Charte, Francisco ; García, Salvador.
Progress in Artificial Intelligence. 8 (2018) 1 - p. 1-14 , 2018

Link: https://doi.org/10.1007/..

11

Tips, guidelines and tools for managing multi-label dataset..:

Charte, Francisco ; Rivera, Antonio J. ; Charte, David..
Neurocomputing. 289 (2018) - p. 68-85 , 2018

Link: https://doi.org/10.1016/..

12

Reducing Data Complexity using Autoencoders with Class-info..:

Charte, David ; Charte, Francisco ; Herrera, Francisco
http://arxiv.org/abs/2111.06142. , 2021

Link: http://arxiv.org/abs/211..

13

Revisiting Data Complexity Metrics Based on Morphology for ..:

Pascual-Triana, José Daniel ; Charte, David ; Arroyo, Marta Andrés..
http://arxiv.org/abs/2007.07935. , 2020

Link: http://arxiv.org/abs/200..

14

An analysis on the use of autoencoders for representation l..:

Charte, David ; Charte, Francisco ; del Jesus, María J.
http://arxiv.org/abs/2005.10516. , 2020

Link: http://arxiv.org/abs/200..

15

COVIDGR Dataset and COVID-SDNet Methodology for Predicting ..:

Tabik, Siham ; Gómez-Ríos, Anabel ; Martín-Rodríguez, José Luis...
https://doi.org/10.1109/JBHI.2020.3037127. , 2020

Link: http://hdl.handle.net/10..