Activity recognition, wearable devices, machine learning

  • Z. Zhu, H.F. Satizabal, U. Blanke, A. Perez-Uribe, and G. Tröster, « Naturalistic Recognition of Activities and Mood using Wearable Electronics », IEEE. Transactions on Affective Computing (to appear, 2015).
  • H.F. Satizabal and A. Perez-Uribe, Unsupervised template discovery in activity recognition using the Gamma Growing Neural Gas algorithm, Soft Computing, Springer Verlag, November 2014, pp. 1-11.
  • J. Rebetez, H.F. Satizabal, A. Perez-Uribe, “Reducing User Intervention in Incremental Activity Recognition for Assistive Technologies”, , Proceedings of the 17th Annual International Symposium on International Symposium on Wearable Computers (ISWC’2013). ACM, New York, NY, USA, pp. 29-32.
  • B. Delachaux, J. Rebetez, A. Perez-Uribe and H.F. Satizabal, “Indoor activity recognition by combining one-vs-all neural network classifiers exploiting wearable and depth sensors”, Rojas, G. Joya, and J. Cabestany (Eds.): IWANN 2013, Part II, LNCS 7903, pp. 216-223, 2013.
  • H.F. Satizabal, J. Rebetez and A. Perez-Uribe, “Semi-Supervised Discovery of Time-Series Templates for Gesture Spotting in Activity Recognition”, Proceedings if the 2nd International Conference in Pattern Recognition Applications and Methods, Barcelona, 2013.

Agroecological modeling, artificial neural networks

  • Satizabal, H.F., Barreto-Sanz, M., Jimenez. D., Perez-Uribe, A., and Cock James, “Enhancing Decision-Making Processes of Small Farmers in Tropical Crops by Means of Machine Learning Models“, Technologies and Innovation for Development, Chapter 18, 2012, pp. 265-277.
  • Carmen Cianfrani, Gwenaëlle Le Lay, Luigi Maiorano, Héctor F. Satizábal, Anna Loy, Antoine Guisan, “Adapting global conservation strategies to climate change at the European scale: The otter as a flagship species“, Biological Conservation 144(8):2068-2080, August 2011.
  • Daniel Jimenez, James Cock, Andy Jarvis, James Garcia, Hector F. Satizabal, Patrick Van Damme, Andres Perez-Uribe, Miguel A. Barreto-Sanz, Interpretation of commercial production information: A case study of lulo (Solanum quitoense), an under-researched Andean fruit, Agricultural Systems, Volume 104, Issue 3, March 2011, Pages 258-270.
  • Satizabal H.F., Perez-Uribe, A.., and Tomassini M. “Avoiding Prototype Proliferation in Incremental Vector Quantization of Large Heterogeneous Datasets”, Studies in Computational Intelligence series, Springer Verlag, Vol 258, 2009, pp. 243-260
  • Daniel Jimenez, James Cock, H.F. Satizabal, Miguel Barreto, Andres Perez-Uribe, Andy Jarvis and Patrick Van Damme, “Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data”, Computer and Eletronics in Agriculture, Elsevier, Vol 69, 2009, pp. 198-208
  • Héctor F. Satizábal, Andrés Pérez-Uribe, Marco Tomassini, “Prototype Proliferation in the Growing Neural Gas Algorithm“, Artificial Neural Networks – ICANN 2008, 18th International Conference, Prague, Czech Republic, September 3-6, 2008.
  • Jiménez Daniel, Pérez-Uribe Andrés, Satizábal Héctor, Barreto Miguel, Van Damme Patrick, Tomassini Marco, “A Survey of Artificial Neural Network-Based Modeling in Agroecology“, Soft Computing Applications in Industry, pp.247-269, February, 2008.
  • Héctor F. Satizábal, Daniel R. Jiménez R, Andrés Pérez-Uribe, “Consequences of Data Uncertainty and Data Precision in Artificial Neural Network Sugar Cane Yield Prediction“, Computational and Ambient Intelligence, 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebastián, Spain, June 20-22, 2007.

Autonomous robots, artificial intelligence

  • H.F. Satizabal, A. Upegui, A. Perez-Uribe, F. Mondada and P. Retornaz, A Social Approach for Target Localization: Simulation and Implementation in the marXbot Robot, Memetic Computing, Springer Verlag, Vol. 3, No 4, 2011, pp. 245-259.
  • Andres Upegui, Yann Thoma, Héctor F. Satizábal, Francesco Mondada, Philippe Rétornaz, Yoan Graf, Andrés Pérez-Uribe, Eduardo Sanchez, “Ubichip, Ubidule, and MarXbot: A Hardware Platform for the Simulation of Complex Systems“, Evolvable Systems: From Biology to Hardware – 9th International Conference, ICES 2010, York, UK, September 6-8, 2010.
  • Héctor F. Satizábal, Andres Upegui, Andrés Pérez-Uribe, “Social Target Localization in a Population of Foragers“, Nature Inspired Cooperative Strategies for Optimization, NICSO 2010, May 12-14, 2010.
  • Héctor F. Satizábal, Andres Upegui, “Dynamic Partial Reconfiguration of the Ubichip for Implementing Adaptive Size Incremental Topologies“, Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2009, Trondheim, Norway, 18-21 May, 2009.

In-vitro neural activity classification, feature extraction, neural networks

  • A. Perez-Uribe and H.F. Satizabal, “Artificial Neural Networks and Data Compression Statistics for the Discrimination of Cultured Neuronal Activity“, LNCS, vol. 7552, 2012, pp. 201-208

Artificial Neural networks

  • Héctor F. Satizábal,  Andrés Pérez-Uribe, “Relevance Metrics to Reduce Input Dimensions in Artificial Neural Networks“, Artificial Neural Networks – ICANN 2007, 17th International Conference, Porto, Portugal, September 9-13, 2007.

March, 2016