2 citations · 3 across the 7 of their papers we have counts for
8 papers
Dynamic Semantic Compression for CNN Inference in Multi-access Edge Computing: A Graph Reinforcement Learning-based Autoencoder
Nan Li, Alexandros Iosifidis, Qi Zhang
This paper studies the computational offloading of CNN inference in dynamic multi-access edge computing (MEC) networks. To address the uncertainties in communication time and compu…
Spatiotemporal Attention-based Semantic Compression for Real-time Video Recognition
Nan Li, Mehdi Bennis, Alexandros Iosifidis +1
This paper studies the computational offloading of video action recognition in edge computing. To achieve effective semantic information extraction and compression, following seman…
Semantic Communication Enabling Robust Edge Intelligence for Time-Critical IoT Applications
Andrea Cavagna, Nan Li, Alexandros Iosifidis +1
This paper aims to design robust Edge Intelligence using semantic communication for time-critical IoT applications. We systematically analyze the effect of image DCT coefficients o…
Design and Prototyping Distributed CNN Inference Acceleration in Edge Computing
Zhongtian Dong, Nan Li, Alexandros Iosifidis +1
For time-critical IoT applications using deep learning, inference acceleration through distributed computing is a promising approach to meet a stringent deadline. In this paper, we…
Attention-based Feature Compression for CNN Inference Offloading in Edge Computing
Nan Li, Alexandros Iosifidis, Qi Zhang
This paper studies the computational offloading of CNN inference in device-edge co-inference systems. Inspired by the emerging paradigm semantic communication, we propose a novel a…
Graph Reinforcement Learning-based CNN Inference Offloading in Dynamic Edge Computing
Nan Li, Alexandros Iosifidis, Qi Zhang
This paper studies the computational offloading of CNN inference in dynamic multi-access edge computing (MEC) networks. To address the uncertainties in communication time and Edge…
Distributed Deep Learning Inference Acceleration using Seamless Collaboration in Edge Computing
Nan Li, Alexandros Iosifidis, Qi Zhang
This paper studies inference acceleration using distributed convolutional neural networks (CNNs) in collaborative edge computing. To ensure inference accuracy in inference task par…
Receptive Field-based Segmentation for Distributed CNN Inference Acceleration in Collaborative Edge Computing
Nan Li, Alexandros Iosifidis, Qi Zhang
This paper studies inference acceleration using distributed convolutional neural networks (CNNs) in collaborative edge computing network. To avoid inference accuracy loss in infere…