According to PWC AI could contribute up to $15.7 trillion to the global economy by 2030 and AI adoption is expected to accelerate during the next years. In our company and business environment we detect a similar trend, an increasing demand from our customers and a market eager to reshape their services and products with AI-based technology.

As regards to AI-based computer vision, our field of expertise, it started to be developed only 7 year ago and since then has been moving fast forward. We’ve been attending to and exhibiting our technology in all past editions of CVPR, ICCV, and ECCV, the world’s top three academic conferences in this field and advances in the last yeares are overwhelming. At the 2019 edition of the conference of computer vision and pattern recognition (CVPR) from a total of 1,300 papers, the most popual areas of research were detaction, segmentation, 3D, and adversarial training. It also shows the growing research in unsupervised learning methods.

Today there are more than 500 million cameras deployed worldwide, making them the largest planet data generatior, 4.3 trillions of hours of video are generated every year, and only a tiny percentage of this video is analyzed with AI, without requiring human monitor. This poses several challenges to cities, governments, companies, and organizations that need to analyze large volumes of video content in an automated and cost-effectively manner, either to monetize this content, enhance security in the community or urban and transportation planning.

At Deep vision AI we apply advanced computer vision technology to understad images and video automatically, turning visual content into real-time analytics and valuable insights. Software solutions are used for different such as safety and security, advanced customer analytics, marketing, and advertising. Our main markets are smart cities, large retail stores, energy & infrastructure, transportation, universities and campuses, banking, sports arenas, gaming and other public venues where safety can be a challenge.

Our Software continuously monitors target zones to provide the count, gender, age and unique identification of individuals over time. Facial Demographics Model is used to understand demographic variations overtime for a designated area of the city, or to track customer patterns such as dwell-time spent in lines or waiting areas of reftail stores. It also helps brands and advertisers to quantify demographics or to target individuals for advertising and product placement. Our Facial Recognition Model tracks unique individuals and provides facial matches for specified individuals. This helpsretailes recognize important customers in real-time, quantifies the frequency of visitors, and improves overall safety and security.

As regards to vehicle recognition, we provide with tehnology that has the ability to count and recognize the year, make, model, color and license plates of vehicles from any angle. Goverments and municiplities use vehicle recognition to automatically analyze vehicle flows and send alarms reporting designated vehicles to law enforcement. The model is also used to infer demographics based on vehicle recognition, quantify vehicle flow, and assess changing traffic patterns. Advertisers and brands also use this information to target contextualized ads based on the changing mix of demographics and to understand ROI of outdoor advertising.

We are strongly convinced that the collaboration is a key to growth and transformation, to do so we have partnered with the world’s leading companies, driving the most innovations in artificial intelligence such as Amazon AWS and Dell. Deep vision computer vision technology can be accessed by more than 200,000 AWS customers through easy to use APIs in the cloud, but it can but it can be also deploued on-premise or at the edge providing with real-time video analytics and supporting most of Nvidia GUP architectures. Deep Vision AI, Dell and Nvidia are providing with advanced video analytics such as facial recognition and vehicle recognation in the smart cities.

Finally, concerns regarding data privacy and GDPR compliance are top priorities for us and our customers, and we apply significant measure to assure a transparent and secure process of the personal data is never compromissed. This includes anonymazation of personal data, in such a way that facial images of non-enrolled subjects are not displayed or visible to users and software operators. and facial information in the video stream is blurred. We encourage our customers and Partners on getting the data subjects’ consent and informing them on their respective rights to protect personal data, and the destined usage of their information under our software and we also encourage them to implement a data loss prevention strategy among other significant measures.

Agustin Caverzasi, Deep vision’s Co-founder & CEO, is an experienced entrepreneur who started his career at a computer vision research group at INRIA Research Center in France. Augustin spent the past 8 years in research and development of computer vision technology, creating customer-centered products and bringing new ideas into the market.


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