Bounding Box
Using rectangular frames to enclose objects to identify location and classify objects in images or videos such as: people, vehicles, objects, states... This is a foundational technique for object recognition and detection tasks.
AI DATA ANNOTATION SERVICE
AI Data Annotation is the core and foundational service within RemoBPO's entire solution ecosystem. We provide high-quality data labeling services to support the training, testing, and optimization of Artificial Intelligence (AI) and Machine Learning models.
From a Business perspective, AI Data Annotation helps businesses:
- Shorten time-to-market for AI products
- Reduce operational costs compared to building an in-house team
- Control data quality risks from the initial stages
From an AI & technical perspective, RemoBPO focuses on building a standardized – tightly controlled – scalable labeling process, ensuring output data achieves high accuracy, consistency, and suitability for each specific AI problem.
Value Delivered
High Accuracy
Increase AI model accuracy and stability
Time Optimization
Shorten training time and model improvement cycles
Standard Compliance
Ensure data meets technical requirements and project standards
RemoBPO Commits
1 Labeling accuracy ≥ 95%
2 Multi-layered QA process
3 Flexibility according to each project and industry requirements
DATA TYPES & TECHNIQUES
RemoBPO possesses the capability to deploy diverse high-tech Data Annotation types, meeting the needs of various AI fields, especially Computer Vision and automated systems. We provide flexible and customizable solutions tailored to each client's specific requirements.
Polyline & Spline
A method for annotating linear structures with high detail. This technique is often applied in labeling lanes, railway tracks, pipelines, transportation infrastructure, and complex-shaped structures.
Segmentation (Pixel-level)
Performing detailed partitioning of each object at the pixel level. Each pixel in the image is specifically labeled, helping the AI model understand the shape, boundaries, and relationships between objects. This technique requires very high accuracy and quality control.
3D Cuboid
Using a 3D cuboid to enclose an object in three-dimensional space. This method is often applied in autonomous vehicles, robotics, and spatial analysis systems, allowing the AI model to estimate the position, size, and distance of objects.
LiDAR Point Cloud
Processing and labeling 3D point cloud data generated by LiDAR technology. This data plays a crucial role in Autonomous Driving, Smart City, and 3D mapping tasks. RemoBPO can annotate LiDAR using various methods such as Bounding Box, 3D Cuboid according to project requirements.
ADVANCED AI DATA PROCESSING SERVICE
In addition to AI Data Annotation, RemoBPO provides Advanced AI Data Processing services, acting as a bridge between raw data and data ready for AI model training.
From a Business perspective, this service helps businesses:
- Reduce resource waste from low-quality data
- Optimize AI training and infrastructure costs
- Ensure consistent input data when scaling projects
Services Include
Data Cleaning & Normalization
Clean and standardize data
Data Validation
Inspect, evaluate, and remove erroneous or non-standard data
Data Structuring
Prepare and structure data according to algorithm requirements
Annotation Guidelines
Develop detailed Data Annotation Guidelines for each project
AI-Specific Optimization
Optimize data for specific AI tasks (Detection, Classification, Segmentation...)
Results Delivered
Through this service, RemoBPO helps clients ensure high-quality input data, minimize deviation risks, and enhance AI model training efficiency.
