Massive amounts of data are generated instantly and as computing power gets increased
subsequently the performance of cloud computing is dissatisfying. The security and privacy …

Deep learning has achieved state-of-the-art performance on several computer vision tasks
and domains. Nevertheless, it still has a high computational cost and demands a significant …

Permanent faults induced due to imperfections in the manufacturing process of Deep Neural
Network (DNN) accelerators are a major concern, as they negatively impact the …

Neuromorphic architectures have seen a resurgence of interest in the past decade owing to
100x-1000x efficiency gain over conventional Von Neumann architectures. Digital …

Deep learning has achieved state-of-the-art performance on several computer vision tasks
and domains. Nevertheless, it still has a high computational cost and demands a significant …

The Capsule Networks (CapsNets) is an advanced form of Convolutional Neural Network
(CNN), capable of learning spatial relations and being invariant to transformations …

The number of mobile robots with constrained computing resources that need to execute
complex machine learning models has been increasing during the past decade. Commonly …

Kurzfassung Im Folgenden werden die Motivation, das Ziel und die Aufgabe der Dissertation
beschrieben. Der herausragende Sieg von AlexNet bei der ImageNet Large Scale …

Stochastic computing (SC) is an unconventional computing style that uses probabilistic
bitstreams to implement algorithms like those for machine learning, digital filtering, and …

In recent years, the proliferation of unmanned aerial vehicles (UAVs) has increased
dramatically. UAVs can accomplish complex or dangerous tasks in a reliable and cost …