The widespread usage of deep neural networks in autonomous driving necessitates a
consideration of the safety arguments against hardware-level faults. This study confirms the …

This survey paper reviews numerous high-level transformation techniques which can be
applied at the algorithm or the architecture level to improve the performance of digital signal …

Pharmaceuticals are chemical compounds employed as medicinal drugs. They have severe
physic-chemical properties which make them destructive for non-target species …

Deep neural networks (DNNs) have proliferated in most of the application domains that
involve data processing, predictive analysis and knowledge inference. Alongside the need …

Focuses on the characterization and classification of reconfiguration techniques. The
techniques are differentiated according to the type of redundancy (time or hardware) …

The efficiency of machine intelligence techniques has improved noticeably in the embedded
application domains thanks to the dedicated hardware accelerators for deep neural …

Parameterized Algorithmics: A Graph-Theoretic Approach Page 1 Parameterized Algorithmics:
A Graph-Theoretic Approach Henning Fernau Universität Tübingen, WSI für Informatik, Sand …

The widespread adoption of deep neural networks in safety-critical systems necessitates the
examination of the safety issues raised by hardware errors. The appropriateness of the …

Fault-Tolerant Parallel Computation presents recent advances in algorithmic ways of
introducing fault-tolerance in multiprocessors under the constraint of preserving efficiency …

S nology and of applications that require extensive throughput. Their realization requires
human ingenuity combined with techniques and tools for algorithm development …