Papers

Title 1: Automatic Modulation Recognition using Deep CNN with Multilevel Fusion Mechanism (Pr)
Target: IEEE Transactions on Cognitive Communications and Networking

Title 2: Deep Learning for Object Detection Using Micro-Doppler Signatures in Autonomous Vehicles (Pr)
Target: KICS winter 2021
Next target: Pattern Recognition Letters (Elsevier)

Title 3: Convolutional Neural Network for Drone Detection and Classification on Edge Devices (Pr)
Target: Signal Processing (Elsevier)

Thesis: Deep Learning-Aided Near-Optimal Modulation Recognition (Pr)
Status: Tentative title

Last Week's Progress

Title 1
[1]. Finetuned a network architecture.
[2]. Tested feature map permutation fusion with the backbone of the network architecture.

Title 2
[1]. Investigated Phased Array System toolbox.
[2]. Performed initial generation of the micro-Doppler signature data.

Title 3
[1]. Researched different lightweight deep learning network architectures.
[2]. Pre-processed the open-source drone detection dataset.

This Week Todo's

Title 1
[1].Finalize the architecture.

Title 2
[1]. Continue with the investigation on the phased array system toolbox.
[2]. Continue with the micro-Doppler signature data generation.

Title 3
[1]. Test the preliminary network architecture.
[2]. Continue with pre-processing of more data samples.

Thesis
[1].Continue with the scope investigation

Project Progress

Anti-Drone

Last Week's Project

[1]. Pre-processed the open-source dataset.
[2]. Worked on LabVIEW communication design toolkit license issues.

This Week's Project

[1]. Continue with the pre-processing of the open-source dataset.
[2]. Continue with the fixing of the communication design toolkit license issues.

Monthly Goals

[1]. Master MATLAB communication, deep learning, and optimization toolboxes.
[2]. Improve the architecture of the title [1] and finalize experiments.
[3]. Start experiments for the winter intensive

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 on NSL technical tools.