Sébastien Jodogne

TL;DR: Evaluation of the methods submitted to the Automatic Cephalometric X-Ray Landmark Detection Challenge provides insights into the performance of different landmark detection approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques.

TL;DR: The textural feature dissimilarity measured on the baseline 18F-FDG PET/CT appears to be a strong independent predictor of the outcome in patients with NSCLC treated by SBRT.

TL;DR: Finite-automata-based algorithms for handling linear arithmetic with both real and integer variables are considered to show, using topological arguments, that only a restricted class of automata on infinite words are necessary for handling real andinteger linear arithmetic.

TL;DR: Finite-automata based algorithms for handling linear arithmetic with both real and integer variables are considered, to show that only a restricted class of automata on infinite words are necessary for handling real andinteger linear arithmetic.

TL;DR: A general, flexible framework for learning mappings from images to actions by interacting with the environment and shows how high-level visual features can be generated when the power of local descriptors is insufficient for completely disambiguating the aliased states.