Data Collection

Design and build unbiased,
field-customized datasets
for training AI models

Data Filtering

The in-house development of
deep learning algorithm-based tools
for data verification,
such as duplication, quality,
and the model suitability of
the collected data

Data Processing

The self-development of
deep learning
algorithm-based tools for
automating annotations
required for AI model training

Model Training

The development of
the face recognition
deep learning model
using the built dataset

Inferencing

GPU/CPU-based
high-performance
face inference model
development