654 citations · 1.5k across the 37 of their papers we have counts for
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Frequency-based Multi Task learning With Attention Mechanism for Fault Detection In Power Systems
Peyman Tehrani, Marco Levorato
The prompt and accurate detection of faults and abnormalities in electric transmission lines is a critical challenge in smart grid systems. Existing methods mostly rely on model-ba…
Split Computing for Complex Object Detectors: Challenges and Preliminary Results
Yoshitomo Matsubara, Marco Levorato
Following the trends of mobile and edge computing for DNN models, an intermediate option, split computing, has been attracting attentions from the research community. Previous stud…
Neural Compression and Filtering for Edge-assisted Real-time Object Detection in Challenged Networks
Yoshitomo Matsubara, Marco Levorato
The edge computing paradigm places compute-capable devices - edge servers - at the network edge to assist mobile devices in executing data analysis tasks. Intuitively, offloading c…
Data-Driven Path Selection for Real-Time Video Streaming at the Network Edge
Sabur Baidya, Peyman Tehrani, Marco Levorato
In this paper, we present a framework for the dynamic selection of the wireless channels used to deliver information-rich data streams to edge servers. The approach we propose is d…
Auction-based Charging Scheduling with Deep Learning Framework for Multi-Drone Networks
MyungJae Shin, Joongheon Kim, Marco Levorato
State-of-the-art drone technologies have severe flight time limitations due to weight constraints, which inevitably lead to a relatively small amount of available energy. Therefore…