Search Results for author:
Found 5 papers, 0 papers with code
An approach to extract information from academic transcripts of HUST
In this paper, we test our improved CRNN model in extracting information from 126 transcripts, with 1008 vertical lines, 3859 horizontal lines, and 2139 handwritten test scores.
Toward BCI-enabled Metaverse: A Joint Learning and Resource Allocation Approach
Our proposed framework involves a mixed decision-making and classification problem in which the base station has to allocate its computing and radio resources to the users and classify the brain signals of users in an efficient manner.
Optimal Power Allocation for Rate Splitting Communications with Deep Reinforcement Learning
This letter introduces a novel framework to optimize the power allocation for users in a Rate Splitting Multiple Access (RSMA) network.
Transferable Deep Reinforcement Learning Framework for Autonomous Vehicles with Joint Radar-Data Communications
Autonomous Vehicles (AVs) are required to operate safely and efficiently in dynamic environments.
Resource Management for Blockchain-enabled Federated Learning: A Deep Reinforcement Learning Approach
However, the issue of BFL is that the mobile devices have energy and CPU constraints that may reduce the system lifetime and training efficiency.
