Identification of speakers
How can I recognize new speakers in my media assets in the future?
Deep Model Customizer
Simplifying AI customization with a powerful no-code AI platform. Drastically reduce training time, costs, and IT-resources.
Trusted by professionals
The Product
Deep Model Customizer solves the limitations and complexities of pre-trained AI models and provides a platform to efficiently manage your training data to create custom AI models with ease while keeping data privacy in mind.
Benefits
No AI expertise required! Skip the search and expense of hiring AI experts. Now, anyone can personalize their own AI models.
Usually, it takes several days or weeks to train standard deep learning algorithms. Deep Model Customizer uses the latest Few-Shot-Learning algorithms, which can be trained with very little data within seconds.
Deep Model Customizer was developed in collaboration with companies that care a lot about data protection. Therefore, your data always stays under your control and can be exported at any time – without vendor locking.
Use cases
How can I recognize new speakers in my media assets in the future?
How can I recognize less-known or regional people in my footage?
Deep Model Customizer
With our face training technology, you can quickly train new faces, making them ready for immediate use in recognition services.
With just a few images, our Landmark Training technology allows you to efficiently train and recognize landmark buildings.
Enhance logo recognition by adding your own logos and training your AI models with just a few clicks to monitor your brand presence online.
Train your speakers effortlessly and intuitively, requiring only minimal data and without the need for negative examples.
Integration & deployment
DeepVA-powered solutions
Success stories
With the help of DeepVA, the user can intuitively and easily create and manage training data directly in the media asset management system (MAM).
Read MoreCreating and managing training data for face recognition using AI requires a lot of time and resources.
Read MoreContact us
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The project has indirectly received funding from the European Commission’s Horizon 2020 Framework Programme through the STADIEM project (Grant Agreement 957321)
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Don’t worry, we reserve our newsletter for important news, so we only send a few updates once in a while. No spam!
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