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Found 14 papers, 1 papers with code
An Adaptive System Architecture for Multimodal Intelligent Transportation Systems
In this paper, we provide an adaptive, user-centric, and layered architecture for multimodal transportation systems.
On the Sum Secrecy Rate Maximisation for Wireless Vehicular Networks
We address these security concerns from a physical layer security aspect by investigating achievable secrecy rates in wireless vehicular networks.
Robustness for Free: Quality-Diversity Driven Discovery of Agile Soft Robotic Gaits
Soft robotics aims to develop robots able to adapt their behavior across a wide range of unstructured and unknown environments.
Myocardial Infarction Detection from ECG: A Gramian Angular Field-based 2D-CNN Approach
Our proposed approach achieves an average classification accuracy of 99. 68\%, 99. 80\%, 99. 82\%, and 99. 84\% under GASF dataset with noise and baseline wander, GADF dataset with noise and baseline wander, GASF dataset with noise and baseline wander removed, and GADF dataset with noise and baseline wander removed, respectively.
Mirror Prox Algorithm for Large-Scale Cell-Free Massive MIMO Uplink Power Control
We consider the problem of max-min fairness for uplink cell-free massive multiple-input multiple-output (MIMO) subject to per-user power constraints.
Massive MIMO for Serving Federated Learning and Non-Federated Learning Users
It is anticipated that future wireless networks will jointly serve both FL and downlink non-FL user groups in the same time-frequency resource.
Serving Federated Learning and Non-Federated Learning Users: A Massive MIMO Approach
We propose a communication scheme that serves the downlink of the non-FL users (UEs) and the uplink of FL UEs in each half of the frequency band.
Power Control for Multigroup Multicast Cell-Free Massive MIMO Downlink
We consider a multigroup multicast cell-free multiple-input multiple-output (MIMO) downlink system with short-term power constraints.
Accelerated Projected Gradient Method for the Optimization of Cell-Free Massive MIMO Downlink
The known methods use off-the-shelf convex solvers, which basically implement an interior-point algorithm, to solve the derived convex problems.
A Low-Complexity Approach for Max-Min Fairness in Uplink Cell-Free Massive MIMO
We consider the problem of max-min fairness for uplink cell-free massive multiple-input multiple-output which is a potential technology for beyond 5G networks.
Utility Maximization for Large-Scale Cell-Free Massive MIMO Downlink
Simulation results for large-scale cell-free massive MIMO show that the four utility functions can deliver nearly uniformed services to all users.
COVID-ResNet: A Deep Learning Framework for Screening of COVID19 from Radiographs
Using these techniques, we showed the state of the art results on the open-access COVID-19 dataset.
Ranked #1 on
Multi-class Classification
on COVID chest X-ray
Learning Rates for Kernel-Based Expectile Regression
Conditional expectiles are becoming an increasingly important tool in finance as well as in other areas of applications.
An SVM-like Approach for Expectile Regression
Expectile regression is a nice tool for investigating conditional distributions beyond the conditional mean.
