Author profile: Mateos García, Daniel
Institutional data
Name | Mateos García, Daniel |
Department | Lenguajes y Sistemas Informáticos |
Knowledge area | Lenguajes y Sistemas Informáticos |
Professional category | Profesor Contratado Doctor |
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Statistics
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No. publications
15
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No. visits
2101
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No. downloads
4924
Publications |
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Article
On the evolutionary weighting of neighbours and features in the k-nearest neighbour rule
(Elsevier, 2019)
This paper presents an evolutionary method for modifying the behaviour of the k-Nearest-Neighbour clas sifier (kNN) called ... |
Presentation
A Preliminary Study of the Suitability of Deep Learning to Improve LiDAR-Derived Biomass Estimation
(Springer, 2016)
Light Detection and Ranging (LiDAR) is a remote sensor able to extract three-dimensional information about forest structure. ... |
Article
An evolutionary voting for k-nearest neighbours
(Elsevier, 2016)
This work presents an evolutionary approach to modify the voting system of the k-nearest neighbours (kNN) rule we called ... |
Article
An evolutionary-weighted majority voting and support vector machines applied to contextual classification of LiDAR and imagery data fusion
(Elsevier, 2015)
Data classification is a critical step to convert remotely sensed data into thematic information. Environmental researchers have ... |
Chapter of Book
Improving the k-Nearest Neighbour Rule by an Evolutionary Voting Approach
(Springer, 2014)
This work presents an evolutionary approach to modify the voting system of the k-Nearest Neighbours (kNN). The main novelty ... |
PhD Thesis
Ponderación local evolutiva de la regla kNN
(2013)
En la literatura, existen numerosas técnicas para mejorar el rendimiento de la regla de los k vecinos más cercanos (en ... |
Article
EVOR-STACK: A label-dependent evolutive stacking on remote sensing data fusion
(Elsevier, 2012)
Land use and land covers (LULC) maps are remote sensing products that are used to classify areas into different landscapes. ... |
Chapter of Book
A Non-parametric Approach for Accurate Contextual Classification of LIDAR and Imagery Data Fusion
(Springer, 2012)
Light Detection and Ranging (LIDAR) has become a very important tool to many environmental applications. This work proposes to ... |
Presentation
Optimizing a Classification System for HEp-2 Cells by Evolutionary Computation
(International Association for Pattern Recognition (IAPR), 2012)
In this work, we describe a classification system to automatically recognize the pattern of HEp-2 cells within IIF images. ... |
Article
On the evolutionary optimization of k-NN by label-dependent feature weighting
(Elsevier, 2012)
Different approaches of feature weighting and k-value selection to improve the nearest neighbour technique can be found ... |
Chapter of Book
A Comparative Study between Two Regression Methods on LiDAR Data: A Case Study
(Springer, 2011)
Airborne LiDAR (Light Detection and Ranging) has become an excellent tool for accurately assessing vegetation characteristics ... |
Chapter of Book
Label Dependent Evolutionary Feature Weighting for Remote Sensing Data
(2010)
Nearest neighbour (NN) is a very common classifier used to develop important remote sensing products like land use and ... |
Chapter of Book
A SVM and k-NN Restricted Stacking to Improve Land Use and Land Cover Classification
(2010)
Land use and land cover (LULC) maps are remote sensing products that are used to classify areas into different landscapes. ... |
Chapter of Book
Statistical Test-Based Evolutionary Segmentation of Yeast Genome
(2004)
Segmentation algorithms emerge observing fluctuations of DNA sequences in alternative homogeneous domains, which are named ... |
Chapter of Book
Evolutionary segmentation of yeast genome
(2004)
Segmentation algorithms differ from clustering algorithms with regard to how to deal with the physical location of genes ... |