100 citations · 148 across the 20 of their papers we have counts for
6 papers · 1 filter
FlocOff: Data Heterogeneity Resilient Federated Learning with Communication-Efficient Edge Offloading
Mulei Ma, Chenyu Gong, Liekang Zeng +2
Federated Learning (FL) has emerged as a fundamental learning paradigm to harness massive data scattered at geo-distributed edge devices in a privacy-preserving way. Given the hete…
A3D: Adaptive, Accurate, and Autonomous Navigation for Edge-Assisted Drones
Liekang Zeng, Haowei Chen, Daipeng Feng +2
Accurate navigation is of paramount importance to ensure flight safety and efficiency for autonomous drones. Recent research starts to use Deep Neural Networks to enhance drone nav…
Real-Time High-Resolution Pedestrian Detection in Crowded Scenes via Parallel Edge Offloading
Hao Wang, Hao Bao, Liekang Zeng +2
To identify dense and small-size pedestrians in surveillance systems, high-resolution cameras are widely deployed, where high-resolution images are captured and delivered to off-th…
CoEdge: Cooperative DNN Inference with Adaptive Workload Partitioning over Heterogeneous Edge Devices
Liekang Zeng, Xu Chen, Zhi Zhou +2
Recent advances in artificial intelligence have driven increasing intelligent applications at the network edge, such as smart home, smart factory, and smart city. To deploy computa…
Knowledge Distillation for Mobile Edge Computation Offloading
Haowei Chen, Liekang Zeng, Shuai Yu +1
Edge computation offloading allows mobile end devices to put execution of compute-intensive task on the edge servers. End devices can decide whether offload the tasks to edge serve…
Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing
En Li, Liekang Zeng, Zhi Zhou +1
As a key technology of enabling Artificial Intelligence (AI) applications in 5G era, Deep Neural Networks (DNNs) have quickly attracted widespread attention. However, it is challen…