A dataset is a collection of image data that is used to build an AI model. In order to recognize content in videos and images, a neural network must learn how, for example, people or objects differ from each other. The AI learns this via so-called sample data, in the form of image data.
Creating and managing a dataset requires a great effort of organization and administration.
In most cases, data sets are managed in different folder structures on internal servers and are very confusing. Using these data sets for training is also often very complicated for customers without administrative knowledge.
DeepVA’s AI solution for image and video recognition enables the automatic assignment of relevant tags or keywords to extensive image and video collections. Our advanced deep-learning models are a core feature of DeepVA’s AI platform, which uses a visual mining technology to analyze images, videos, and live streams on a pixel level, extracting their features and detecting relevant personalities, objects, points of interest, text insertions, and many other relevant features. The AI models have been trained with more than 3,000 objects, over 20,000 personalities, as well as more than 30,000 landmarks and 300,000 logo variations from day-to-day life, and can additionally be individualized with custom tags to achieve the highest accuracy.
With DeepVA, we can help your employees with redundant and complex processes and support your company in building automated and customer-centric products.
faster data acquisition
With DeepVA, we have found a great partner with major know-how in computer vision that carries the latest research data in its DNA. Practicality and interdisciplinarity are very important to us, so we are looking forward to future innovative and exciting projects with DeepVA.
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DeepVA + Medialoopster
Integration of image and video recognition into a MAM
(media asset management) system.