Héctor F. Satizábal

According to our database1, Héctor F. Satizábal authored at least 26 papers between 2007 and 2024.

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

Timeline

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Bibliography

2024
Unveiling the Potential of Synthetic Data in Sports Science: A Comparative Study of Generative Methods.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

2021
Learning Image Segmentation from Few Annotations - A REPTILE Application.
Proceedings of the Advances in Computational Intelligence, 2021

2019
Fruit and Vegetable Information System Using Embedded Convolutional Neural Networks.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2019

2017
ActiDote - A wireless sensor-based system for self-tracking activity levels among manual wheelchair users.
EAI Endorsed Trans. Pervasive Health Technol., 2017

Exploring Internal Representations of Deep Neural Networks.
Proceedings of the Computational Intelligence - 9th International Joint Conference, 2017

Towards a Better Understanding of Deep Neural Networks Representations using Deep Generative Networks.
Proceedings of the 9th International Joint Conference on Computational Intelligence, 2017

DiscoveryTree: Relative localization based on multi-hop BLE beacons.
Proceedings of the Global Internet of Things Summit, 2017

2016
Naturalistic Recognition of Activities and Mood Using Wearable Electronics.
IEEE Trans. Affect. Comput., 2016

EvoBoids: Co-design of a physical and virtual game using Artificial Evolution.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Augmenting a convolutional neural network with local histograms - A case study in crop classification from high-resolution UAV imagery.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

A Wireless Sensor-Based System for Self-tracking Activity Levels Among Manual Wheelchair Users.
Proceedings of the eHealth 360°, 2016

2015
Unsupervised template discovery in activity recognition using the Gamma Growing Neural Gas algorithm.
Soft Comput., 2015

2013
Indoor Activity Recognition by Combining One-vs.-All Neural Network Classifiers Exploiting Wearable and Depth Sensors.
Proceedings of the Advances in Computational Intelligence, 2013

Reducing user intervention in incremental activityrecognition for assistive technologies.
Proceedings of the 17th Annual International Symposium on Wearable Computers. ISWC 2013, 2013

Semi-supervised Discovery of Time-series Templates for Gesture Spotting in Activity Recognition.
Proceedings of the ICPRAM 2013, 2013

2012
Artificial Neural Networks and Data Compression Statistics for the Discrimination of Cultured Neuronal Activity.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

2011
A social approach for target localization: simulation and implementation in the marXbot robot.
Memetic Comput., 2011

Using the GNG-m Algorithm to Deal with the Problem of Catastrophic Forgetting in Incremental Modelling.
Proceedings of the NCTA 2011, 2011

2010
Social Target Localization in a Population of Foragers.
Proceedings of the Nature Inspired Cooperative Strategies for Optimization, 2010

Ubichip, Ubidule, and MarXbot: A Hardware Platform for the Simulation of Complex Systems.
Proceedings of the Evolvable Systems: From Biology to Hardware, 2010

2009
Avoiding Prototype Proliferation in Incremental Vector Quantization of Large Heterogeneous Datasets.
Proceedings of the Constructive Neural Networks, 2009

Dynamic partial reconfiguration of the Ubichip for implementing adaptive size incremental topologies.
Proceedings of the IEEE Congress on Evolutionary Computation, 2009

2008
A Survey of Artificial Neural Network-Based Modeling in Agroecology.
Proceedings of the Soft Computing Applications in Industry, 2008

Prototype Proliferation in the Growing Neural Gas Algorithm.
Proceedings of the Artificial Neural Networks, 2008

2007
Consequences of Data Uncertainty and Data Precision in Artificial Neural Network Sugar Cane Yield Prediction.
Proceedings of the Computational and Ambient Intelligence, 2007

Relevance Metrics to Reduce Input Dimensions in Artificial Neural Networks.
Proceedings of the Artificial Neural Networks, 2007


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