9 citations · 9 across the 2 of their papers we have counts for
3 papers
cs.DC2020
Orpheus: A New Deep Learning Framework for Easy Deployment and Evaluation of Edge Inference
Perry Gibson, José Cano
Optimising deep learning inference across edge devices and optimisation targets such as inference time, memory footprint and power consumption is a key challenge due to the ubiquit…
cs.CV2020★ 9 cited
Accelerating Deep Learning Applications in Space
Martina Lofqvist, José Cano
Computing at the edge offers intriguing possibilities for the development of autonomy and artificial intelligence. The advancements in autonomous technologies and the resurgence of…
cs.LG2020
Optimizing Grouped Convolutions on Edge Devices
Perry Gibson, José Cano, Jack Turner +3
When deploying a deep neural network on constrained hardware, it is possible to replace the network's standard convolutions with grouped convolutions. This allows for substantial m…