In the ‘Software 2.0’ era, we cover the entire lifecycle from architecture establishment to system development and maintenance
based on BrycenKorea’s Software 2.0, Software with AI, for rapid business response of customers and seamless integrated construction and
operation of existing systems and AI big data-based intelligent systems.

It means a ‘comprehensive methodology’ that defines the procedures, outputs, techniques, and tools for creating software in which
code-based software based on traditional software development owned by companies and AI technology-based software of machine
learning/deep learning are organically combined.

2D images captured by cameras, which are the core of computer vision that utilizes various sensing data to increase automation and efficiency,
are processed at high speed in parallel on thousands of processor cores, and shading and depth are added to enable 3D expression.

While applications continue to expand with the spread of multi-camera smartphones, 3D games, and social media, in addition to image processing, ML/DL matrix processing and imaging techniques for optimal image generation to maximize computing performance are currently being used.
Advanced acceleration technology is designed to balance the load between the CPU and GPU, and optimize GPU processing schedules
to reduce overall latency and power consumption of the hardware. Besides low latency and low power consumption,
this technology supports the generation of valuable data.

8K Video Mass Processing

We perform high-speed and pre-processing for machine learning methods such as our DL techniques
(e.g. format conversion, thumbnail generation, data structure understanding, feature composition and other machine learning engine
pre-run data preparation processes) can be used to speed up machine learning analysis.
This allows the use of 4K/8K high-resolution images to speed up the machine learning analysis.

We are developing new technology by combining our technology with 8K video. Utilizing the ultra-high image quality

Combined with image recognition algorithms such as object/person detection, the real-time performance of the entire hardware can be further improved.

Supports functions such as DICOM format support (CT, MRI, 3D image support), 3D rendering, Rectangle Elipse, Freedraw, FixerAreaROI,
ROI modification, ROI deletion, ROI saving, etc.

Optimized for organizing big data that holds large amounts of images, such as automatic object tracking, image classification, object detection,
area classification, tagging, and data management.

Supports functions such as Bbox, Segmentation, Keypoints, Checker mode, etc.