Background and activities
Ricardo da S. Torres is Professor in Visual Computing at the Norwegian University of Science and Technology (NTNU). He used to hold a position as a Professor at the University of Campinas, Brazil (2005 - 2019). Dr. Torres received a B.Sc. in Computer Engineering from the University of Campinas, Brazil, in 2000 and his Ph.D. degree in Computer Science at the same university in 2004. Dr. Torres has been serving as the coordinator of Master Program in Simulation and Visualisation from at NTNU since 08/2020. Dr. Torres has been developing multidisciplinary eScience research projects involving Multimedia Analysis, Multimedia Retrieval, Machine Learning, Databases, Information Visualisation, and Digital Libraries. Dr. Torres is author/co-author of more than 200 articles in refereed journals and conferences and serves as a PC member for several international and national conferences. Currently, he has been serving as Senior Associate Editor of the IEEE Signal Processing Letters and Associate Editor of the Pattern Recognition Letters. He is a member of the IEEE.
- IE501988 - Sustainability Analytics
- IE500217 - Computer Graphics
- IE505818 - Simulation and Visualization, Specialization Course
- AM512030 - Sustainability Analytics
- IE505718 - Simulation and Visualization, Specialization Project
- IE500814 - Dynamic Systems and Control
- IE501914 - Immersive Technologies
Scientific, academic and artistic work
- (2022) Litter Detection with Deep Learning: A Comparative Study. Sensors. vol. 22 (2).
- (2022) Characterization and analyses of dribbling actions in soccer: a novel definition and effectiveness of dribbles in the 2018 FIFA World Cup RussiaTM. Human Movement. vol. 23 (1).
- (2022) A genetic programming approach for searching on nearest neighbors graphs. Multimedia tools and applications.
- (2022) Automatic Markerless Motion Detector Method against Traditional Digitisation for 3-Dimensional Movement Kinematic Analysis of Ball Kicking in Soccer Field Context. International Journal of Environmental Research and Public Health (IJERPH). vol. 19 (3).
- (2021) Sport action mining: Dribbling recognition in soccer. Multimedia tools and applications.
- (2021) Multiscale fractal dimension applied to tactical analysis in football: A novel approach to evaluate the shapes of team organization on the pitch. PLOS ONE. vol. 16 (9).
- (2021) Football player dominant region determined by a novel model based on instantaneous kinematics variables. Scientific Reports. vol. 11 (1).
- (2021) Complex network model indicates a positive effect of inspiratory muscles pre-activation on performance parameters in a judo match. Scientific Reports. vol. 11 (1).
- (2021) Non-technical Loss Detection in Power Grid Using Information Retrieval approaches: A Comparative Study. IEEE Access. vol. 9.
- (2021) Contextual movement models based on normalizing flows. AStA Advances in Statistical Analysis.
- (2021) On the prediction of long-lived bugs: An analysis and comparative study using FLOSS projects. Information and Software Technology. vol. 132 (106508).
- (2021) Classification and determinants of passing difficulty in soccer: a multivariate approach. Science and medicine in football.
- (2021) Comparing CAM Algorithms for the Identification of Salient Image Features in Iconography Artwork Analysis. Journal of Imaging.
- (2021) A BFS-Tree of ranking references for unsupervised manifold learning. Pattern Recognition. vol. 111.
- (2021) A genetic algorithm approach for image representation learning through color quantization. Multimedia tools and applications. vol. 80.
- (2021) Measuring Economic Activity From Space: A Case Study Using Flying Airplanes and COVID-19. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. vol. 14.
- (2021) Cognitive control-loop for elastic optical networks with space-division multiplexing. Sensors. vol. 21 (23).
- (2020) A Soft Computing Approach for Selecting and Combining Spectral Bands. Remote Sensing. vol. 12 (14).
- (2020) Detecting face presentation attacks in mobile devices with a patch-based CNN and a sensor-aware loss function. PLOS ONE. vol. 15 (9).
- (2020) Relationship between maximal aerobic power with aerobic fitness as a function of signal-to-noise ratio. Journal of applied physiology. vol. 129 (3).