Juan Miguel Ortiz-de-Lazcano-Lobato

According to our database1, Juan Miguel Ortiz-de-Lazcano-Lobato authored at least 48 papers between 2004 and 2020.

Collaborative distances:
  • Dijkstra number2 of six.
  • Erdős number3 of five.

Timeline

Legend:

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PhD thesis 
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Bibliography

2020
Background subtraction by probabilistic modeling of patch features learned by deep autoencoders.
Integr. Comput. Aided Eng., 2020

Deep Autoencoder Architectures For Foreground Object Detection In Video Sequences Based On Probabilistic Mixture Models.
Proceedings of the IEEE International Conference on Image Processing, 2020

Foreground Detection by Probabilistic Mixture Models Using Semantic Information from Deep Networks.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019
Foreground detection by probabilistic modeling of the features discovered by stacked denoising autoencoders in noisy video sequences.
Pattern Recognit. Lett., 2019

Motion detection with low cost hardware for PTZ cameras.
Integr. Comput. Aided Eng., 2019

Background Modeling by Shifted Tilings of Stacked Denoising Autoencoders.
Proceedings of the From Bioinspired Systems and Biomedical Applications to Machine Learning, 2019

2018
Deep learning-based anomalous object detection system powered by microcontroller for PTZ cameras.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Background Modeling for Video Sequences by Stacked Denoising Autoencoders.
Proceedings of the Advances in Artificial Intelligence, 2018

2017
A Growing Neural Gas Approach to Classify Vehicles in Traffic Environments.
Int. J. Comput. Vis. Image Process., 2017

Motion Detection by Microcontroller for Panning Cameras.
Proceedings of the Biomedical Applications Based on Natural and Artificial Computing, 2017

Vehicle Classification in Traffic Environments Using the Growing Neural Gas.
Proceedings of the Advances in Computational Intelligence, 2017

2013
A Competitive Neural Network for Multiple Object Tracking in Video Sequence Analysis.
Neural Process. Lett., 2013

2011
Dynamic topology learning with the probabilistic self-organizing graph.
Neurocomputing, 2011

Choice effect of linear separability testing methods on constructive neural network algorithms: An empirical study.
Expert Syst. Appl., 2011

Feature Weighting in Competitive Learning for Multiple Object Tracking in Video Sequences.
Proceedings of the Advances in Computational Intelligence, 2011

2010
An anomaly detection system using a GHSOM-1.
Proceedings of the International Joint Conference on Neural Networks, 2010

2009
Analysis and Testing of the <i>m</i>-Class RDP Neural Network.
Proceedings of the Constructive Neural Networks, 2009

MREM, Discrete Recurrent Network for Optimization.
Proceedings of the Encyclopedia of Artificial Intelligence (3 Volumes), 2009

Probabilistic PCA Self-Organizing Maps.
IEEE Trans. Neural Networks, 2009

Automatic Model Selection by Cross-Validation for Probabilistic PCA.
Neural Process. Lett., 2009

Dynamic Competitive Probabilistic Principal Components Analysis.
Int. J. Neural Syst., 2009

Hierarchical Graphs for Data Clustering.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

Probabilistic Self-Organizing Graphs.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

Nonparametric Location Estimation for Probability Density Function Learning.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

Growing Competitive Network for Tracking Objects in Video Sequences.
Proceedings of the Adaptive and Natural Computing Algorithms, 9th International Conference, 2009

Object Tracking in Video Sequences by Unsupervised Learning.
Proceedings of the Computer Analysis of Images and Patterns, 13th International Conference, 2009

2008
Soft clustering for nonparametric probability density function estimation.
Pattern Recognit. Lett., 2008

Robust Nonparametric Probability Density Estimation by Soft Clustering.
Proceedings of the Artificial Neural Networks, 2008

On the Generalization of the m-Class RDP Neural Network.
Proceedings of the Artificial Neural Networks, 2008

2007
Stochastic Functional Annealing as Optimization Technique: Application to the Traveling Salesman Problem with Recurrent Networks.
Proceedings of the KI 2007: Advances in Artificial Intelligence, 2007

Theoretical Study on the Capacity of Associative Memory with Multiple Reference Points.
Proceedings of the Bio-inspired Modeling of Cognitive Tasks, 2007

Self-organization of Probabilistic PCA Models.
Proceedings of the Computational and Ambient Intelligence, 2007

Automatic Model Selection for Probabilistic PCA.
Proceedings of the Computational and Ambient Intelligence, 2007

Two Pages Graph Layout Via Recurrent Multivalued Neural Networks.
Proceedings of the Computational and Ambient Intelligence, 2007

Image Compression with Competitive Networks and Pre-fixed Prototypes.
Proceedings of the Artificial Intelligence and Innovations 2007: from Theory to Applications, 2007

A Study into the Improvement of Binary Hopfield Networks for Map Coloring.
Proceedings of the Adaptive and Natural Computing Algorithms, 8th International Conference, 2007

Improved Production of Competitive Learning Rules with an Additional Term for Vector Quantization.
Proceedings of the Adaptive and Natural Computing Algorithms, 8th International Conference, 2007

Soft Clustering for Nonparametric Probability Density Function Estimation.
Proceedings of the Artificial Neural Networks, 2007

<i>K</i> -Pages Graph Drawing with Multivalued Neural Networks.
Proceedings of the Artificial Neural Networks, 2007

A Novel and Efficient Method for Testing Non Linear Separability.
Proceedings of the Artificial Neural Networks, 2007

2006
Local Selection of Model Parameters in Probability Density Function Estimation.
Proceedings of the Artificial Neural Networks, 2006

Image Compression by Vector Quantization with Recurrent Discrete Networks.
Proceedings of the Artificial Neural Networks, 2006

Enhanced maxcut clustering with multivalued neural networks and functional annealing.
Proceedings of the ESANN 2006, 2006

Global-local learning strategies in probabilistic principal components analysis.
Proceedings of the Artificial Intelligence and Soft Computing, 2006

2005
Hopfield Network as Associative Memory with Multiple Reference Points.
Proceedings of the International Enformatika Conference, 2005

Intrinsic Dimensionality Maps with the PCASOM.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

2004
Principal Components Analysis Competitive Learning.
Neural Comput., 2004

Dynamic Selection of Model Parameters in Principal Components Analysis Neural Networks.
Proceedings of the 16th Eureopean Conference on Artificial Intelligence, 2004


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