Our research is applied to various industries and focuses on making human life happier.
We are working on accelerating computational processing of artificial neural networks, deep learning object recognition, LiDAR scanning and augmented reality fusion.
By integrating the scanning LiDAR sensor and the camera, the augmented reality monitoring can be implemented as a work environment recognition and space detection in the unmanned automation and automation of automobile and construction equipment.
LiDAR scanning technology utilizes the advantage of laser that can generate pulse signal with high energy density and short cycle, so it can collect 3D image information including accurate physical property observation and distance information, And is developing into a wide range of industrial applications such as unmanned vehicles, robots, and 3D video cameras.
Using 360° non-rotating LiDAR sensor and signal processing technology for real-time environment detection,
 LiDAR system (KETI) |
 Laser Scanner with multi-layer technology |
Deep learning operation for real-time traffic object image recognition acceleration is implemented in RTL-based FPGA to improve detection rate and efficiency of power consumption, and to prevent traffic accidents at intersections and crosswalks.
Provides advanced traffic safety service by automatically detecting and controlling pedestrian and peripherals based on deep running and big data.
Provides high speed, real-time efficiency, scalability and flexibility by accelerating algorithms while minimizing power consumption based on FPGA.
