VISUAL FACE INTELLIGENCE
State-of-the-art of face recognition and face demographics has shown significant progress by the evolution of deep learning, due to their superb learning capacity approaching human-level performance. This motivates DeepVision’s team to continuously research and apply advances on the field to it’s visual recognition technology.
From detecting and recognizing faces either from images or videos, and by performing face demographics like age, gender, ethnicity and emotions recognition, DeepVision’s technology allows customers to organize his data, present personalized content, perform search from visual content, build security systems, and more:
DeepVision’s visual recognition use cases:
Tag and organize
- Tag users easily and automatically organize and group information based on users names, ages, genders, ethnicities or emotions at specific times or even in real time.
- Find particular users in images or find specific appearances in videos by applying search based on users names, and other information like age, gender, ethnicity and expressions.
- Perform visual search to compare users directly from the images, or find other users with similar characteristics either in images or videos.
- Perform user analytics to increase engagement through content personalization, understand users preferences, or improve shoppers experiences based on users visual information.
- Perform authentication from users faces to build security systems either for access control, enrollment systems, and more.