The activity of the Signal, Image and Sound Team (SIMS) is in the field of statistical signal and image processing. The research work carried out by the team members is based on methodological questions most often inspired by applied problems from a wide variety of fields, such as physics, biology, health, engineering and industrial instrumentation.
The evolution of the requirements of decision support systems, in terms of accuracy and reliability, has led to the diversification of measurement and data acquisition methods. This multi-modality is a source of increasingly large amounts of data, whose processing by conventional methods often faces obstacles that result in either too long a computation time or too much memory space. At the same time, the growth in the capacities of computing processors offers an opportunity for processing this data, provided that new processing methods are available that ensure a better match between the resulting algorithms and the available computing tools, as well as the ability to exploit any structure intrinsic to the data.
The design of such methods, based on proven mathematical tools, is the main challenge facing the SIMS team.
The first two themes (Reverse problems, Machine learning) are rather methodological: which model to use? which representation to choose? which estimator to calculate ? which criterion to minimize? while the third (Mathematical and numerical tools) is rather algorithmic: how to perform the calculation in an acceptable time and in an efficient way? Most of the team's research activities are inspired by the need to offer solutions adapted to signal and image processing in multidisciplinary application areas such as biomedical (brain-computer interface, prosthesis control, dignostic aid), multimedia (audio content analysis, sound design) and instrumentation (non-destructive testing, airborne or satellite remote sensing, biological imaging).