Papers

Title 1: Fire Disaster Notification Management (FDNM) for Military Storage and Supply Operation Centers
Published: Proceedings of ICTC 2019

Title 2: Delay-aware Computation Offloading Based-on Task Segmentation for IIoT System (A)
Published: Proceedings of KICS fall 2019

Title 3: Optimal Relay Selection Scheme for Mobile-Fog Enabled Cyber-Physical Systems.
Target: Not fixed

Title 4: Sparsely Connected CNN for Efficient Automatic Modulation Recognition
Target: IEEE Transactions on Vehicular Technology
Submitted: July 1, 2020 (Original paper)
Re-submitted (Revised paper): Oct 6, 2020
Status (Revised paper): With the Associate editor

Title 5: Multi-shuffled Convolutional Blocks for Low complex Modulation Recognition (A)
Target: ICTC 2020
Submitted: Aug 15, 2020
Status: Accepted
Date: 13/09/2020

Title 6: Learning Spatiotemporal Features by using CNN for efficient Modulation Recognition (A)
Target: KICS summer 2020
Status: Accepted

Title 7: Automatic Modulation Recognition using Deep CNN with Multilevel Attention Mechanism (Pr)
Target: Not fixed

Last Week's Progress

Title 4
[1]. Awaiting the review comments.

Title 5
[1]. Prepared the conference report.

Title 6
[1]. Awaiting the publication.

Title 7
[1]. Experiments.
[2]. Continue with finetuning the network architecture.
[3]. Literature review on low complexity CNN architectures

This Week Todo's

Title 4
[1]. Awaiting the review comments.

Title 5
[1]. Awaiting the publication.

Title 6
[1]. Awaiting the publication.

Title 7
[1]. Continue with Experiments.
[2]. Finetuning the network architecture.
[3]. Apply the ideas from the the literatures to modify the current architecture.
[4]. Test the effect of grouped normalization to the initial layers.
[5]. Investigate the idea of hyperparameter optimization.

Project Progress

Anti-Drone

Last Week's Project

[1]. Literature review on the low complex Deep learning architectures.
[2]. Worked on the USSRP module on LabVIEW module to accept multiple channels.

This Week's Project

[1]. Literature review on the low complex Deep learning architectures.
[2]. Continue on the USSRP module on LabVIEW module to accept multiple channels.

Monthly Goals

[1]. Master MATLAB communication, deep learning, and optimization toolboxes.
[2]. Improve the algorithm and finalize experiments of the summer intensive.
[3]. Finish the LabVIEW USSRP module modules and Start RF data collection for the Anti-drone project.
[4]. Prepare the dataset and idea for winter intensive and KICS winter conference

Annual Goals

[1]. To submit at least one paper to the SCI journal.
[2]. Attend international and domestic conferences recommended by NSL.
[3]. Acquiring knowledge and skills of NSL technical tools.