Computer Vision

Computer Vision Description
  • Facial Attendance System - FAS
Our facial recognition system is based on competitive and high technology with various applicable potentialities, and it possesses great advantages such as accuracy, efficiency and user-friendliness. Getting along with face recognition evolution trend, our expert team in machine learning has successfully developed FAS.

APPLICABLE AREAS
• Main Gate: Factory, Building, Hospital, Supper-market, Commercial center, etc.
• Small Room: Office, Class-room, Cashier, Laboratory, Secure place.


  • Smart Port Vision System - SPVS
There are a lot of CCTV cameras installed in container terminal area that can be used for many purposes. With the power of Deep Learning technologies we can apply for the smart port system projects. It can be applied to the below fields:
• STS Loading/Discharging CNTR No. Recognition
• STS Lane & YT Number Recognition
• Human Safety Detection
• Terminal CCTV Monitoring
• Human Activity Detection
STS Loading/Discharging CNTR No. Recognition

STS Lane & YT Number Recognition


Human Safety Detection
Terminal CCTV Monitoring
Human Activity Detection


  • Shipping Instruction Information Auto Extraction
There are a lot of Shipping Instruction (SI) need to be processed and inputted into the system and take a lot of time with current manual input. We have developed the solution that can extract the data from these documents and input to the system automatically with very high accuracy and reduce significant manual time.
• Various PDF document data can be extracted and converted to a certain user-defined format and saved in database.
• Verified solution with high accuracy, flexibility and efficiency.




  • Other Object Detection Application
MOTION RECOGNITION
Motion recognition is one of the most important segments of human-centered researches. Getting along with the development in artificial intelligence, deep learning techniques have obtained a number of essential achievements in computer vision and also been adopted to motion recognition.