Publications

Activity recognition, wearable devices, machine learning

  • Ricardo Muñoz Bocanegra, Jesús Alfonso López, Héctor Satizabal and Andrés Pérez Uribe, “Fruit and Vegetable Information System Using Embedded Convolutional Neural Networks“, 2019 IEEE LA-CCI Conference (accepted)
  • Richoz, S., Perez-Uribe, A., Birch, P., & Roggen, D.. “Benchmarking deep classifiers on mobile devices for vision-based transportation recognition.” In Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers, 2019, pp. 803-807
  • Sebastien Richoz, Mathis Ciliberto, Lin Wang, Philip Birch, Hristijan Gjoreski, Andres Perez-Uribe, and Daniel Roggen, “Human and Machine Recognition of Transportation Modes from Body-Worn Camera Images“, Proceedings of Activity and Behavior Computing Conference, 2019 (to appear)
  • Andres Perez-Uribe, Hector-Fabio Satizabal-Mejia, « High-level activity recognition for cognitive support in older adults», In FTAL conference on Industrial Applied Data Science, Lugano, 18-19 October, 2018, pp. 9-10
  • Sabbani Imad, Perez-Uribe Andres, Bouattane Omar, El Moudni Abdellah, « Deep convolutional neural network architecture for urban traffic flow estimation », International Journal of Computer Science and Network Security, Vol 18, No 7, 2018, pp. 69-75
  • Chabloz, Olivier, David Da Silva Ändrade, Andres Upegui, Hector F. Satizábal, and Andres Perez-Uribe. “DiscoveryTree: Relative localization based on multi-hop BLE beacons.” In 2017 Global Internet of Things Summit (GIoTS), pp. 1-6. IEEE, 2017.
  • H. Satizabal, A. Grillon, A. Upegui, G. Millet, G. Picasso, A. Perez-Uribe, “ActiDote – A wireless sensor-based system for self-tracking activity levels among manual wheelchair users”, EAI Endorsed Transactions on Pervasive Health and Technology, 17(12): e5, 2017
  • A. Grillon, A. Perez-Uribe, H. Satizabal, L. Gantel, D. Da Silva Andrade, A. Upegui, and F. Degache, “A wireless sensor-based system for self-tracking activity levels among manual wheelchair users“, eHealth 360°, Volume 181 of the series Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Springer International Publishing, Dec. 1, 2016, pp 229-240
  • Zhu, Zack, Héctor F. Satizábal, Ulf Blanke, Andres Perez-Uribe, and Gerhard Tröster. “Naturalistic recognition of activities and mood using wearable electronics.” IEEE Transactions on Affective Computing 7, no. 3 (2016): 272-285.
  • 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, remote sensing, neural networks

  • Andres Perez-Uribe, Hector-Fabio Satizabal-Mejia, Julien Rebetez, « Big Data system for pantropical land- cover change monitoring », In FTAL conference on Industrial Applied Data Science, Lugano, 18-19 October, 2018, pp. 20-21
  • Julien Rebetez, Hector F. Satizabal, Matteo Mota, Dorothea Noll, Lucie Büchi, Marina Wendling, Bertrand Cannelle, Andres Perez-Uribe and Stéphane Burgos, “Augmenting a convolutional neural network with local histograms – A case study in crop classification from high-resolution UAV imagery” , Proceedings of the European Symposium on Artificial Neural Networks, ESANN’16.
  • Reymondin, Louis, et al. “A methodology for near real-time monitoring of habitat change at continental scales using MODIS-NDVI and TRMM.” Submitted Remote Sensing of Environment.
  • 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.
  • 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.
  • Barreto, M., Perez-Uribe, A., Pena-Reyes, C.A., and Tomassini M. “Tuning Parameters in the Fuzzy Growing Hierarchical Self-Organizing Networks”, Studies in Computational Intelligence series, Springer Verlag, Vol 258, 2009, pp. 261-280
  • 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, Hector 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
  • Sae-Tang A., Perez-Uribe, A., Jarvis A., “Artificial Neural Network Models for Identifying Novelties in Vegetation Time Series”, The 6th European Conf. on Ecological Modelling, Trieste, Italy. November 27-30, 2007, pp. 452-453.

Autonomous robots, artificial intelligence

  • González, Francisco J., Héctor F. Satizábal, Andres Perez-Uribe, and Jesús A. López. “DCGAN Model Used To Generate Body Gestures On a Human-Humanoid Interaction System.” In 2019 IEEE Colombian Conference on Applications in Computational Intelligence (ColCACI), pp. 1-5. IEEE, 2019.
  • Andres Perez-Uribe, Hector Fabio Satizabal-Mejia, Francisco Gonzales Lopez, « Endowing humanoid robots with the capability of reading and reacting to human body language », In FTAL conference on Industrial Applied Data Science, Lugano, 18-19 October, 2018, pp. 38-39
  • Alvarez-Charris, David C., Andrés Pérez-Uribe, Héctor F. Satizábal, and Jesús A. Lopez. “EvoBoids: Co-design of a physical and virtual game using Artificial Evolution” In Computational Intelligence (SSCI), 2016 IEEE Symposium Series on, pp. 1-8. IEEE, 2016.
  • A. Pérez-Uribe, « Les chercheurs en IA rêvent-ils de robots SF ? “, Catalogue de l’exposition « Portrait-Robot » du musée La Maison d’Ailleurs, June 2015
  • 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.

Gamification

  • A. Perez-Uribe, « Les jeux comme moteur du progrès scientifique », CultureEnJeu magazine, No 54, 2017.
  • Andres Perez-Uribe, Grégoire Aubert, Julien Rebetez, Alexandre Grillon, Hector Satizabal, and Louis Reymondin, « Forest Defenders: Have fun while fighting deforestation », 2nd Gamification and Serious Game Symposium, Neuchatel, June 30-July 1, 2017, pp. 73-74.

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.

Complete list of publications (until 2018)

October, 2019