11 citations · 23 across the 3 of their papers we have counts for
4 papers
Computational Intelligence and Deep Learning for Next-Generation Edge-Enabled Industrial IoT
Shunpu Tang, Lunyuan Chen, Ke HeJunjuan Xia +2
In this paper, we investigate how to deploy computational intelligence and deep learning (DL) in edge-enabled industrial IoT networks. In this system, the IoT devices can collabora…
Learning based signal detection for MIMO systems with unknown noise statistics
Ke He, Le He, Lisheng Fan +3
This paper aims to devise a generalized maximum likelihood (ML) estimator to robustly detect signals with unknown noise statistics in multiple-input multiple-output (MIMO) systems.…
Towards Optimally Efficient Search with Deep Learning for Large-Scale MIMO Systems
Le He, Ke He, Lisheng Fan +3
This paper investigates the optimal signal detection problem with a particular interest in large-scale multiple-input multiple-output (MIMO) systems. The problem is NP-hard and can…
FeCaffe: FPGA-enabled Caffe with OpenCL for Deep Learning Training and Inference on Intel Stratix 10
Ke He, Bo Liu, Yu Zhang +2
Deep learning and Convolutional Neural Network (CNN) have becoming increasingly more popular and important in both academic and industrial areas in recent years cause they are able…