This paper presents the real-time model checker RAVEN and related theoretical background. RAVEN augments the efficiency of traditional symbolic model checking with possibilities to...
We study the problem of classifying images into a given, pre-determined taxonomy. The task can be elegantly translated into the structured learning framework. Structured learning, ...
Abstract. We propose a highly automated approach to the point correspondence problem for anatomical shapes in medical images. Manual landmarking is performed on a small subset of t...
Pre-execution attacks cache misses for which conventional address-prediction driven prefetching is ineffective. In pre-execution, copies of cache miss computations are isolated fr...
A tool that automates the floating-point to fixed-point conversion (FFC) process for digital signal processing systems is described. The tool automatically optimizes fixed-point d...