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Today's market is brimming with extraordinary mobile apps that are not only fostering intelligence but are creating a personalized experience for users too. The examples are countless, right from The WAZE Traffic Navigation app that feeds you the best route in real-time with help from fellow drivers; to the OVAL MONEY App that creates a money-saving strategy that's smart and easy for you to follow. In this blog post, we are going to discuss the most popular ML frameworks and the industries that use mobile vision technology in the development of mobile apps. Learn more about Mobile Vision APIs here

Learn how Embedded Vision combines Embedded Systems and Computer Vision together to enable a machine to perform intelligent tasks.

Face recognition can be used not just for authentication but also surveillance as well. Most security-conscious organizations such as banking & financial institutions, Government, Airports, have been using advanced facial recognition technology to add a layer of security at their premises. For example- Dubai Airport uses it to strengthen security as well as reducing check-in time. Hospitals are using this technology to deliver better care in terms of protecting patient privacy, ensuring accurate insurance benefits, and connecting a face with a name, which in turn, provides another option for identification besides the date of birth. The Mastercard Identity check even leverages this technology for payment confirmation.

KritiKal offers best-in-class services and solutions in Artificial Intelligence (AI), Data Science and Analytics. This includes extracting intelligence and insights from data such as images, videos, audio, text etc, and enabling suitable actions.

KritiKal built a safe load indicator unit using different sensors that monitor the system as per the configured safety limits and gather relevant data.