Federated learning is a distributed machine learning approach where loca...
Path planning is a crucial component for realizing the autonomy of mobil...
A practical issue of edge AI systems is that data distributions of train...
Federated learning is a machine learning method in which data is not
agg...
Point cloud registration is the basis for many robotic applications such...
In real-world edge AI applications, their accuracy is often affected by
...
A computing cluster that interconnects multiple compute nodes is used to...
Although high-performance deep neural networks are in high demand in edg...
Currently there has been increasing demand for real-time training on
res...
SLAM allows a robot to continuously perceive the surrounding environment...
ODENet is a deep neural network architecture in which a stacking structu...
An efficient hardware design of Simultaneous Localization and Mapping (S...
DQN (Deep Q-Network) is a method to perform Q-learning for reinforcement...
Most edge AI focuses on prediction tasks on resource-limited edge device...
Semi-supervised anomaly detection is referred as an approach to identify...
Key-value store is a popular type of cloud computing applications. The
p...