108 citations · 234 across the 37 of their papers we have counts for
7 papers · 1 filter
DroNet: Efficient convolutional neural network detector for real-time UAV applications
Christos Kyrkou, George Plastiras, Stylianos Venieris +2
Unmanned Aerial Vehicles (drones) are emerging as a promising technology for both environmental and infrastructure monitoring, with broad use in a plethora of applications. Many su…
CascadeCNN: Pushing the Performance Limits of Quantisation in Convolutional Neural Networks
Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis
This work presents CascadeCNN, an automated toolflow that pushes the quantisation limits of any given CNN model, aiming to perform high-throughput inference. A two-stage architectu…
Deploying Deep Neural Networks in the Embedded Space
Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis
Recently, Deep Neural Networks (DNNs) have emerged as the dominant model across various AI applications. In the era of IoT and mobile systems, the efficient deployment of DNNs on e…
CascadeCNN: Pushing the performance limits of quantisation
Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis
This work presents CascadeCNN, an automated toolflow that pushes the quantisation limits of any given CNN model, to perform high-throughput inference by exploiting the computation…
f-CNN: A Toolflow for Mapping Multi-CNN Applications on FPGAs
Stylianos I. Venieris, Christos-Savvas Bouganis
The predictive power of Convolutional Neural Networks (CNNs) has been an integral factor for emerging latency-sensitive applications, such as autonomous drones and vehicles. Such s…
Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions
Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis
In the past decade, Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance in various Artificial Intelligence tasks. To accelerate the experimentation…
Approximate FPGA-based LSTMs under Computation Time Constraints
Michalis Rizakis, Stylianos I. Venieris, Alexandros Kouris +1
Recurrent Neural Networks and in particular Long Short-Term Memory (LSTM) networks have demonstrated state-of-the-art accuracy in several emerging Artificial Intelligence tasks. Ho…