Papers

Title 1: Automatic Modulation Recognition using Deep CNN with Multilevel Fusion Mechanism (Pr)
Target: IEEE Signal Processing Letters

Title 2: Deep Learning for Object Detection Using Micro-Doppler Signatures in Autonomous Vehicles (Pr)
Target: KICS winter 2021

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 in Power-Constrained Devices (Pr)
Status: Tentative title

Last Week's Progress

Title 1
[1]. Experiments and finetuned the architecture.
[3]. Investigated hyperparameter optimization and feature map permutation.

Title 2
[1]. Submitted.

Title 3
[1]. Investigated different Machine learning methodologies for drone detection.
[2]. Investigated the feasibility of methodologies on edge devices.

This Week Todo's

Title 1
[1]. Continue with Experiments.
[2]. Finetuning a network architecture.
[3]. Continue with the Investigation on hyperparameter optimization & feature map permutation.

Title 2
[1]. Start the extension for submission into a journal.

Title 3
[1]. Continue with the methodology.
[2]. Start exploratory data analysis based on open-source datasets.

Project Progress

Anti-Drone

Last Week's Project

[1]. Literature review on the low-complex Deep learning architectures.
[2]. Start pre-processing the open-source dataset.
[3]. To continue fixing the LabVIEW communication design toolkit license issues.

This Week's Project

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

Monthly Goals

[1]. Master MATLAB communication, deep learning, and optimization toolboxes.
[2]. Improve the algorithm of title [1] and finalize experiments.
[3]. Finish the LabVIEW USSRP module and Start RF data collection for the Anti-drone project.

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.