Title 2: Enhanced Deep Learning Scheme Based On PANet for Real-Time Detection of Tomato
Diseases.
Target: IEEE Intelligent Systems (Under Review)
Title 3: Hierarchical Intrusion Detection System for Secured Military Drone Network: A Perspicacious
Approach
Target: MILCOM 2022 (Accepted)
Title 4: VisioNET Dataset: An Aerial Dataset for Scenario-Based Multi-Drone Detection and Identification
Research (Anti-drone project)
Target: IEEE Transactions on Aerospace and Electronic Systems
Title 5: Scalable Out-of-Core Learning Model for Intrusion Detection System on the Internet of Drones
Target: KICS Summer 2022 (Accepted)
Title 6: Scale Variant Framework for Aerial Recognition of Drones and Birds in Ground-to-Air Networks
Target: IET Computer Vision (Rejected)
Title 7: Cyber Edge Intelligent Intrusion Detection Framework For UAV Network Based on Random Forest
Algorithm
Target: ICTC 2022 (Accepted)
Title 8: Efficient Intrusion Detection Model for Securing the Communication Links of Internet of Drone Network (Summer Intensive)
Target: IEEE Internet of Things / Journal of Computer Network
Title 2: Under review
Title 3: Working on review comments while preparing for the conference.
Title 6: Improve paper based on review comments received and submit to another journal.
Title 7: Prepare presentation slides
Title 8: Completed paper
Lectures:
i. Install and start learning the R environments
Title 2: Under review
Title 3: Still enhancing paper based on reviewers’ recommendations.
Title 6: Paused paper revision until next week
Title 7: Prepare presentation slides
Title 8: Working on review comments received from senior colleagues
Lectures:
i. Completed R installation and commenced working with it for big data analysis
ii. Attend lectures and respond to assignments
iii. Attend thesis research sessions with Professor
iv. Prepare for graduation examination
Anti-Drone System
i. Brainstormed with team members on the current roadmap of anti-drone project
ii. Received task allocation based on team leader’s intuition
i. Begin studying on Radar and Sniffing technologies for drone detections.
ii. Survey papers and gather knowledge on hybrid techniques for robust drone detection
i.Complete and submit summer intensive paper for possible publication (80%)
ii. Effect changes and improve Title 7 for resubmission
iii. Acquire in-depth knowledge of the various ML and DL algorithms (75% progress)
iv. Become proficient in the use of OpenCV for object detection and tracking in real-time (paused)
v. Begin and excel on the journey to R programming
vi. Successfully write my graduation exams
i. Submission of at least 3 journals
ii. Become an AI expert in both ML and DL techniques