ssr: Semi-Supervised Regression Methods. An R package. E. Garcia-Ceja.


  • User Adaptive Models for Activity and Emotion Recognition using Deep Transfer Learning and Data Augmentation. E. Garcia-Ceja, M. Riegler, Anders Kvernberg, J. Torresen. User Modeling and User-Adapted Interaction Journal, 2019 (accepted).
  • One-Dimensional Convolutional Neural Networks on Motor Activity Measurements in Detection of Depression. J. Ihle Frogner, F. Majeed Noori, P. Halvorsen, S. Hicks, E. Garcia-Ceja, J. Torresen and M. Riegler. 4th International Workshop on Multimedia for Personal Health and Health Care (HealthMedia) 2019.
  • User Recognition Based on Daily Actigraphy Patterns. E. Garcia-Ceja, B. Morin. 13th International Conference on Trust Management (IFIPTM), 2019.
  • Amplifying Integration Tests with CAMP. F. Chauvel, B. Morin, E. Garcia-Ceja. The 30th International Symposium on Software Reliability Engineering (ISSRE), 2019.
  • Fusion of Multiple Representations Extracted from a Single Sensor's Data for Activity Recognition Using CNNs. F. Majeed Noori, E. Garcia-Ceja, M. Z. Uddin, M. Riegler and J. Torresen. The 2019 International Joint Conference on Neural Networks (IJCNN), 2019.
  • Motor Activity Based Classification of Depression in Unipolar and Bipolar Patients. E. Garcia-Ceja, M. Riegler, P. Jakobsen, J. Torresen., T. Nordgreen, K. Oedegaard, O. Bernt. 31st IEEE CBMS International Symposium on Computer-Based Medical Systems, 2018.
  • Activity Recognition with a cellphone´s accelerometer. Garcia-Ceja, E. & R. Brena. COMIA 2011, Avances Recientes en Sistemas Inteligentes, M. Gonzalez, Oscar Herera (eds.), ISBN 978-607-95367-3-2, pp. 103-112, Sociedad Mexicana de Inteligencia Artificial, México, 2011. (in spanish)