Research
- Research
- Embedded System
Embedded System
Our focus in the field of Embedded Systems lies in combining hardware and software to enhance the overall system's performance and reliability. Through our research, we aim to optimize data processing on the hardware side and improve resource efficiency and performance on the software side.
AI Applied Embedded System
In the domain of AI Applied Embedded Systems, we aim to effectively integrate cutting-edge AI algorithms like CNN, RNN, SNN, and Transformer with FPGA, utilizing limited computing resources for low-power and real-time operation. Additionally, we research sensor and FPGA performance enhancements. Our goal is to implement highly efficient and optimized systems across diverse fields.
Our focus:
- Enhancing object recognition system for improved object detection in a wide illumination range.
- Deep learning-based eye-tracking embedded system.
- Hardware-software optimization for edge computing.
AI Semiconductor
In the AI Semiconductor domain, Understanding the operation of AI applications and utilizing advanced transistor processes and design techniques, we aim to design semiconductors optimized for AI platforms. Our goal is to elevate the performance and energy efficiency of AI applications by optimizing the entire system.
Our focus:
- Semiconductor design for high-performance AI computations.
- Development of edge computing technology using AI semiconductors.
- Optimization of neuromorphic semiconductor implementation for artificial neural networks.