V prosinci 2012 jsem v laboratoři LISSI na univerzitě Université Paris-Est Créteil v Paříži obhájil svou doktorskou práci. Její abstrakt si můžete přečíst níže a její plný text si můžete stáhnout zde: Doktorská práce Dominik M. Ramík (PDF, 5,6MB). Vedoucím mé práce by profesor Kurosh Madani a tutorem mi byl doktor Christophe Sabourin. Více o mém životě v Paříži v průběhu doktorských studií si můžete přečíst na stránce o mých cestách.
Contribution to Complex Visual Information Processing and Autonomous Knowledge Extraction: Application to Autonomous Robotics
Abstract: The work accomplished in this thesis concerns development of an autonomous machine cognition system. The proposed solution reposes on the assumption that it is the curiosity which motivates a cognitive system to acquire new knowledge. Further, two distinct kinds of curiosity are identified in conformity to human cognitive system. On this I build a two level cognitive architecture. I identify its lower level with the perceptual saliency mechanism, while the higher level performs knowledge acquisition from observation and interaction with the environment. This thesis brings the following contribution: A) Investigation of the state of the art in autonomous knowledge acquisition. B) Realization of a lower cognitive level in the ensemble of the mentioned system, which is realizing the perceptual curiosity mechanism through a novel fast, real-world robust algorithm for salient object detection and learning. C) Realization of a higher cognitive level through a general framework for knowledge acquisition from observation and interaction with the environment including humans. Based on the epistemic curiosity, the high-level cognitive system enables a machine (e.g. a robot) to be itself the actor of its learning. An important consequence of this system is the possibility to confer high level multimodal cognitive capabilities to robots to increase their autonomy in real-world environment (human environment). D) Realization of the strategy proposed in the context of autonomous robotics. The studies and experimental validations done had confirmed notably that our approach allows increasing the autonomy of robots in real-world environment.