Skip to content
View FIVEYOUNGWOO's full-sized avatar
23 followers · 7 following

Achievements

Achievement: Pull SharkAchievement: Galaxy BrainAchievement: Pair ExtraordinaireAchievement: QuickdrawAchievement: Public Sponsor

Achievements

Achievement: Pull SharkAchievement: Galaxy BrainAchievement: Pair ExtraordinaireAchievement: QuickdrawAchievement: Public Sponsor

Block or report FIVEYOUNGWOO

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
FIVEYOUNGWOO/README.md

Introduction:

Mostly interested in multimodal AI, reinforcement learning-based optimization, RF sensing, and 5G/B5G. Also working for applications of smart solutions (integrated IoT/ICT with deep neural nets) in computer vision and wireless communication.

Recent projects:

Lately leading a lab project as "multimodal AI-based human mobility detection, tracking, and motion estimation". The suggested idea is to utilize WiFi signal characteristics to improve camera-based detection and tracking performance. In addition, responsible for newly multimodal and DL/ML algorithms to apply our proposed approach.

Preferred programming Languages:

  • Python
  • Java
  • C/C++
  • LabVIEW
  • MATLAB

Preferred programming Frameworks:

  • PyTorch/TensorFlow
  • Open AI Gym/StableBaselines
  • LabVIEW Communications Application Frameworks/LabVIEW FPGA
  • Android Studio

Educational Backgrounds:

  • M.S. in Department of Computer Engineering, Chosun University.
  • B.S. in Department of Computer Engineering, Chosun University (Summa cum Laude).

Popular repositories Loading

  1. DQN-Based-Power-Allocation-For-Multi-Cell-Massive-MIMO DQN-Based-Power-Allocation-For-Multi-Cell-Massive-MIMO Public

    Deep Q network-based power allocation for multi-cell massive MIMO cellular network.

    Jupyter Notebook 15 7

  2. Reinforcement-Learning-Based-MIMO-Antenna-Selection Reinforcement-Learning-Based-MIMO-Antenna-Selection Public

    DQN, DDQN, and Policy Gradient Algorithm-Based Antenna Selection Schemes in MIMO Systems.

    Jupyter Notebook 10 3

  3. Tranditional-MIMO-Antenna-Selection Tranditional-MIMO-Antenna-Selection Public

    Tranditional MIMO antenna selection schemes in MATLAB.

    MATLAB 8

  4. IEEE-802.11n-CSI-Camera-Synchronization-Toolkit IEEE-802.11n-CSI-Camera-Synchronization-Toolkit Public

    IEEE 802.11n CSI and camera synchronization toolkit.

    C 8 4

  5. LMS-Algorithm-Based-Adaptive-Equalizer-For-Digital-Communications LMS-Algorithm-Based-Adaptive-Equalizer-For-Digital-Communications Public

    Least Mean Squares-Based Adaptive Digital Equalizer in Labview NXG.

    7

  6. Advantage-Actor-Critic-Based-MIMO-Antenna-Selection Advantage-Actor-Critic-Based-MIMO-Antenna-Selection Public

    Advanced actor-critic-based antenna selection for MIMO systems.

    Jupyter Notebook 7 1