face dataset creation

Automatic creation of training data for individual needs

our solution

Automatic and fast building of training data

In order for an AI to learn and then automatically recognize content, you need to provide it with training data, e.g. sample images and videos.

In effect, the machine learning algorithms will enable the computer to teach itself about the context of visual data by automatically extracting information such as people’s faces and their names from videos and livestreams. As a result, the Face Dataset Creation AI links these pieces of information together and stores them in a ready to use dataset. You can then use it to automate the mundane and time-consuming task of manually labeling your images, letting you focus on more important and complex assignments.

Frame by frame analysis

DeepVA examines and evaluates every frame individually.

Creation of datasets from unidentified individuals

The Face Dataset Recognition uses interview scenes to extract all necessary information and store it in datasets.

Fast set up of datasets

You only need one sample image to train your AI model.

Evaluation of the data

The Face Dataset Recognition ensures that generated sample images are suitable for the creation of an AI model.

dataset creation benefits

Why should media companies use
Face Dataset Creation

Fast output of training data

Your first tool to create training data in seconds

Easy to train

No programming skills necessary – just select the visual assets you want to train and push the button

Runs everywhere

Works both on-premise and on your cloud platform — you choose the best option for your business

Huge savings

Save up to 98% of time and 87% of costs by automating the training data process

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