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José-Luis Sancho-Gómez
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2020 – today
- 2022
- [j32]Khalil Bousbai
, Juan Morales-Sánchez
Improving hand gestures recognition capabilities by ensembling convolutional networks. Expert Syst. J. Knowl. Eng. 39(5) (2022) - [j31]Rafael Berenguer-Vidal
Decision Trees for Glaucoma Screening Based on the Asymmetry of the Retinal Nerve Fiber Layer in Optical Coherence Tomography. Sensors 22(13): 4842 (2022) - [c25]María-Elena Fernández-García
Double-Layer Stacked Denoising Autoencoders for Regression. IWINAC (1) 2022: 337-345 - 2021
- [j30]Adrián Sánchez-Morales, José-Luis Sancho-Gómez
Complete autoencoders for classification with missing values. Neural Comput. Appl. 33(6): 1951-1957 (2021) - [j29]María-Elena Fernández-García
Complete Stacked Denoising Auto-Encoders for Regression. Neural Process. Lett. 53(1): 787-797 (2021) - [c24]Mohamed Chouai
Autoencoder and Modified YOLOv3 Based Firearms Object Detection in X-ray Baggage Images to Enhance Aviation Safety. SOCO 2021: 338-347 - 2020
- [j28]Juan-Antonio Martínez-García
Designing non-linear minimax and related discriminants by disjoint tangent configurations applied to RBF networks. Neurocomputing 383: 106-112 (2020) - [j27]Siham Tabik, Ricardo F. Alvear-Sandoval, María M. Ruiz, José-Luis Sancho-Gómez
MNIST-NET10: A heterogeneous deep networks fusion based on the degree of certainty to reach 0.1% error rate. Ensembles overview and proposal. Inf. Fusion 62: 73-80 (2020) - [j26]Mohamed Chouai
Supervised feature learning by adversarial autoencoder approach for object classification in dual X-ray image of luggage. J. Intell. Manuf. 31(5): 1101-1112 (2020) - [j25]Juan-Antonio Martínez-García
Performance analysis of No-Propagation and ELM algorithms in classification. Neural Comput. Appl. 32(17): 13183-13193 (2020) - [j24]Adrián Sánchez-Morales, José-Luis Sancho-Gómez
Improving deep learning performance with missing values via deletion and compensation. Neural Comput. Appl. 32(17): 13233-13244 (2020) - [c23]Sina Ahmadi, John Philip McCrae, Sanni Nimb, Anas Fahad Khan, Monica Monachini, Bolette S. Pedersen, Thierry Declerck, Tanja Wissik, Andrea Bellandi, Irene Pisani, Thomas Troelsgård, Sussi Olsen, Simon Krek, Veronika Lipp, Tamás Váradi, László Simon, András Gyorffy, Carole Tiberius, Tanneke Schoonheim, Yifat Ben Moshe, Maya Rudich, Raya Abu Ahmad, Dorielle Lonke, Kira Kovalenko, Margit Langemets, Jelena Kallas, Oksana Dereza, Theodorus Fransen, David Cillessen, David Lindemann, Mikel Alonso, Ana Salgado, José-Luis Sancho, Rafael-J. Ureña-Ruiz, Jordi Porta Zamorano, Kiril Simov, Petya Osenova, Zara Kancheva, Ivaylo Radev, Ranka Stankovic, Andrej Perdih, Dejan Gabrovsek:
A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment. LREC 2020: 3232-3242 - [c22]Mohamed Chouai, Mostefa Merah, José-Luis Sancho-Gómez
A machine learning color-based segmentation for object detection within dual X-ray baggage images. NISS 2020: 50:1-50:11 - [i1]Siham Tabik, Ricardo F. Alvear-Sandoval, María M. Ruiz, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Francisco Herrera:
A tutorial on ensembles and deep learning fusion with MNIST as guiding thread: A complex heterogeneous fusion scheme reaching 10 digits error. CoRR abs/2001.11486 (2020)
2010 – 2019
- 2019
- [j23]Adrián Sánchez-Morales, José-Luis Sancho-Gómez
Exploiting label information to improve auto-encoding based classifiers. Neurocomputing 370: 104-108 (2019) - [j22]Ricardo F. Alvear-Sandoval, José-Luis Sancho-Gómez
On improving CNNs performance: The case of MNIST. Inf. Fusion 52: 106-109 (2019) - [c21]María-Elena Fernández-García
Machine-Health Application Based on Machine Learning Techniques for Prediction of Valve Wear in a Manufacturing Plant. IWINAC (2) 2019: 389-398 - 2018
- [j21]José-Luis Sancho-Gómez
Linear discriminants described by disjoint tangent configurations. Neurocomputing 316: 345-356 (2018) - 2017
- [j20]Andrés Bueno-Crespo
Bioinspired Architecture Selection for Multitask Learning. Frontiers Neuroinformatics 11: 39 (2017) - [c20]Adrián Sánchez-Morales, José-Luis Sancho-Gómez
Values Deletion to Improve Deep Imputation Processes. IWINAC (2) 2017: 240-246 - 2016
- [j19]Rosa-María Menchón-Lara
Early-stage atherosclerosis detection using deep learning over carotid ultrasound images. Appl. Soft Comput. 49: 616-628 (2016) - 2015
- [j18]María Consuelo Bastida Jumilla, Rosa-María Menchón-Lara
Frequency-domain active contours solution to evaluate intima-media thickness of the common carotid artery. Biomed. Signal Process. Control. 16: 68-79 (2015) - [j17]Rosa-María Menchón-Lara
Fully automatic segmentation of ultrasound common carotid artery images based on machine learning. Neurocomputing 151: 161-167 (2015) - [j16]María Consuelo Bastida Jumilla, Jorge Larrey-Ruiz, Rafael Verdú Monedero
Erratum to: DRR and Portal Image Registration for Automatic Patient Positioning in Radiotherapy Treatment. J. Digit. Imaging 28(2): 127 (2015) - [c19]Rosa-María Menchón-Lara
Using Machine Learning Techniques for the Automatic Detection of Arterial Wall Layers in Carotid Ultrasounds. ISAmI 2015: 193-201 - [c18]Andrés Bueno-Crespo
Related Tasks Selection to Multitask Learning Schemes. IWINAC (2) 2015: 213-221 - [c17]Rosa-María Menchón-Lara
Estimation of the Arterial Diameter in Ultrasound Images of the Common Carotid Artery. IWINAC (1) 2015: 358-367 - 2014
- [j15]Jorge Larrey-Ruiz, Juan Morales-Sánchez
Automatic image-based segmentation of the heart from CT scans. EURASIP J. Image Video Process. 2014: 52 (2014) - [j14]Rosa-María Menchón-Lara
Automatic detection of the intima-media thickness in ultrasound images of the common carotid artery using neural networks. Medical Biol. Eng. Comput. 52(2): 169-181 (2014) - [c16]Rosa-María Menchón-Lara
Ultrasound image processing based on machine learning for the fully automatic evaluation of the Carotid Intima-Media Thickness. CBMI 2014: 1-4 - [c15]Jordi Porta, José-Luis Sancho
Using Maximum Entropy Models to Discriminate between Similar Languages and Varieties. VarDial@COLING 2014: 120-128 - 2013
- [j13]Pedro J. García-Laencina, José-Luis Sancho-Gómez
Classifying patterns with missing values using Multi-Task Learning perceptrons. Expert Syst. Appl. 40(4): 1333-1341 (2013) - [j12]María Consuelo Bastida Jumilla, Rosa-María Menchón-Lara
Segmentation of the Common Carotid Artery Walls Based on a Frequency Implementation of Active Contours - Segmentation of the Common Carotid Artery Walls. J. Digit. Imaging 26(1): 129-139 (2013) - [j11]Andrés Bueno-Crespo
Neural architecture design based on extreme learning machine. Neural Networks 48: 19-24 (2013) - [c14]Rosa-María Menchón-Lara
Measurement of Carotid Intima-Media Thickness in ultrasound images by means of an automatic segmentation process based on machine learning. EUROCON 2013: 2086-2093 - [c13]Rosa-María Menchón-Lara
Automatic Evaluation of Carotid Intima-Media Thickness in Ultrasounds Using Machine Learning. IWINAC (2) 2013: 241-249 - [c12]Jordi Porta, José-Luis Sancho
Word Normalization in Twitter Using Finite-state Transducers. Tweet-Norm@SEPLN 2013: 49-53 - 2012
- [j10]Daniel Urda
WIMP: Web server tool for missing data imputation. Comput. Methods Programs Biomed. 108(3): 1247-1254 (2012) - [j9]Andrés Bueno-Crespo
Improving learning by using artificial hints. Neurocomputing 79: 18-25 (2012) - 2011
- [j8]María Consuelo Bastida Jumilla, Jorge Larrey-Ruiz, Rafael Verdú Monedero
DRR and Portal Image Registration for Automatic Patient Positioning in Radiotherapy Treatment. J. Digit. Imaging 24(6): 999-1009 (2011) - [c11]Rosa-María Menchón-Lara
Segmentation of the Carotid Artery in Ultrasound Images Using Neural Networks. IWINAC (2) 2011: 463-471 - 2010
- [j7]Pedro J. García-Laencina, José-Luis Sancho-Gómez
Pattern classification with missing data: a review. Neural Comput. Appl. 19(2): 263-282 (2010) - [c10]María Consuelo Bastida Jumilla, Juan Morales-Sánchez
Detection of the intima and media walls of the carotid artery with geodesic active contours. ICIP 2010: 2213-2216
2000 – 2009
- 2009
- [j6]José-Luis Sancho-Gómez
Combining Missing Data Imputation and Pattern Classification in a Multi-Layer Perceptron. Intell. Autom. Soft Comput. 15(4): 539-553 (2009) - [j5]Pedro J. García-Laencina, José-Luis Sancho-Gómez
K nearest neighbours with mutual information for simultaneous classification and missing data imputation. Neurocomputing 72(7-9): 1483-1493 (2009) - [c9]María Consuelo Bastida Jumilla, Juan Morales-Sánchez
Measurements over the Aquiles Tendon through Ecographic Images Processing. IWINAC (2) 2009: 1-10 - 2008
- [c8]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Michel Verleysen:
K-nearest neighbours based on mutual information for incomplete data classification. ESANN 2008: 37-42 - 2007
- [c7]Jesús Serrano-García, Pedro J. García-Laencina, Jorge Larrey-Ruiz, José-Luis Sancho-Gómez
A Support Vector Method for Estimating Joint Density of Medical Images. IWINAC (2) 2007: 162-170 - [c6]Pedro J. García-Laencina, Jesús Serrano-García, Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez
Multi-task Neural Networks for Dealing with Missing Inputs. IWINAC (1) 2007: 282-291 - [c5]Andrés Bueno-Crespo
Multitask Learning with Data Editing. IWINAC (1) 2007: 320-326 - 2006
- [c4]Pedro J. García-Laencina, José-Luis Sancho-Gómez
Pattern Classification with Missing Values using Multitask Learning. IJCNN 2006: 3594-3601 - 2005
- [c3]Juan Morales-Sánchez
Multiple feature models for image matching. ICIP (3) 2005: 1076-1079 - [c2]Pedro J. García-Laencina, Aníbal R. Figueiras-Vidal, Jesús Serrano-García, José-Luis Sancho-Gómez
Exploiting Multitask Learning Schemes Using Private Subnetworks. IWANN 2005: 233-240 - 2003
- [j4]Junshui Ma, José-Luis Sancho-Gómez
Nonlinear multiclass discriminant analysis. IEEE Signal Process. Lett. 10(7): 196-199 (2003) - 2001
- [j3]Jesús Cid-Sueiro
Saturated Perceptrons for Maximum Margin and Minimum Misclassification Error. Neural Process. Lett. 14(3): 217-226 (2001) - 2000
- [j2]José-Luis Sancho, William E. Pierson, Batu Ulug, Aníbal R. Figueiras-Vidal, Stanley C. Ahalt:
Class separability estimation and incremental learning using boundary methods. Neurocomputing 35(1-4): 3-26 (2000) - [c1]Manel Martínez-Ramón, José-Luis Sancho-Gómez, Antonio Artés-Rodríguez, Aníbal R. Figueiras-Vidal:
Adaptive combination of LMS and logistic-linear equalizers to improve the speed-performance compromise. EUSIPCO 2000: 1-4
1990 – 1999
- 1999
- [j1]Abdelouahid Lyhyaoui, Manel Martínez-Ramón, Inma Mora, Maryan Vaquez, José-Luis Sancho
Sample selection via clustering to construct support vector-like classifiers. IEEE Trans. Neural Networks 10(6): 1474-1481 (1999)
Coauthor Index
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