Training Data Creation Platform
For AI (Machine Learning / Deep Learning)
Annotation One produced by Global Walkers, Inc.
High quality and low cost! Provides a wide variety of training data.
Less than 1/3 in-house costs by offshore use
More than 10 times work speed with a specialized team
In a high security environment in compliance with ISO27001
*According to our research, results differ depending on the work content and work team structure.
3D Bounding Box (Cuboid)
Movie / Tracking
3D Bounding Box (Cuboid)
Movie / Tracking
We also develop and tune our AI models, and use this knowledge to advise on how to improve the accuracy of AI models, and build highly accurate and low-cost operations for our clients.
What Is Annotation?
Annotation originally refers to adding relevant information (metadata) as “annotations” to certain data.
In AI development, it means “tagging” training data (labeling data) to make machine learning and deep learning models smarter.
For example, tagging a photo of a person with the tags as “person,” “face,” and “arm,” or tagging a person with the tag as “woman,” such tagging work is called “annotation work.”
Unless AI learns by a set of “image” and “tag information” for the image just like above, it will not be able to understand what the image is.
Features of “Annotation One”
“Annotation One” provides comprehensive support to solve all issues that arise in the process of creating training data.
01How do we create training data?
Even if you know that annotation data is necessary for creating an AI model, there are various types of target data and methods of annotation to choose from. In addition, how much the training data should be ready varies depending on what your AI model needs to learn.
We can also give advice on training data creation based on our knowledge of AI development.
02No time or resources to create training data!
Engineer resources to develop AI models are precious. Even when in-house resources are available, the monotonous annotation task of training data tends to be put off.
At Global Walkers, our dedicated annotation operators teams can help you create high-quality training data in a short time.
03Decided on the AI to create, but no training data!
There is often a case that you have determined on the AI model to be developed, but you have no image material for the training data at hand.
We are available to collect images from the web or support in photographing at a studio. Moreover, we can also reduce the number of images you need to prepare by using a technique called “Data Augmentation,” augmenting training data.
Training data creation services provided by “Annotation One”
High-quality annotation data (training data) is manually created for machine learning and deep learning.
We will assist you in creating the most appropriate client original dataset to meet your individual needs.
We not only create training data for static images, but also perform annotation task for various types of data, including 3D (three-dimensional) images and movies.
Data Check / Modification
In some cases, you may end up modifying the outsourced annotation data due to its poor quality, or may have a limitation to the amount of the data to annotate because of insufficient resources for data check. As a solution for these matters, we also offer services for data check and modification only.
We create image and video data based on the specifications of the AI model you are developing and the contents of hearings on the required training data. We support you from booking a studio or shooting location to shooting. We also support data creation using computer graphics.
We select images for training data from commercially available data sources. We provide high quality and transparent data sources that clear portrait rights.
How “Annotation One” Works in an AI Project
It doesn’t stop once. To cope with AI that advances day by day,
AI development support based on the “Human In The Loop” model brings AI detection closer to 100%.
01Training Data Creation
02AI Model Training
03Evaluation of AI Model
04 Modification / Additional Creation of Training Data