Wipro Limited

Arun Jeyaprasad Arjun Jeyarani

Maheshwaran Govindarajeswaran

Sudipta Ghosh

Systems and methods for recommending content to a user based on the user's interests are described herein. In one example, the method comprises receiving at least one image of the user, and analyzing the at least one image to determine one or more facial attributes of the user. The method further comprises processing the at least one image to determine the gaze parameters of the user, determining based on the gaze parameters, an object of interest of the user and retrieving the characteristics of the object of interest. The method further comprises ascertaining, based on the facial attributes, an emotional index associated with the user, and generating recommendations of the content for the user based in part on the emotional index and characteristics of the object of interest.

System and method for recommending content to a user based on user's interest

The present disclosure provides methods for concurrently executing ordered and unordered tasks using a plurality of processing units. Certain embodiments of the present disclosure may store the ordered and unordered tasks in the same processing queue. Further, processing tasks in the processing queue may comprise concurrently preprocessing ordered tasks, thereby reducing the amount of processing unit idle time and improving load balancing across processing units. Embodiments of the present disclosure may also dynamically manage the number of processing units based on a rate of unordered tasks being received in the processing queue, a processing rate of unordered tasks, a rate of ordered tasks being received in the processing queue, a processing rate of ordered tasks, and/or the number of sets of related ordered tasks in the processing queue. Also provided are related systems and non-transitory computer-readable media.

Method and system for efficient execution of ordered and unordered tasks in multi-threaded and networked computing

Systems, methods, and non-transitory computer readable media for determining the emotional state of a user are described herein. In one example, the method for determining the emotional state of the user comprises receiving a feed from a sensor at a default sampling frequency, and analyzing the feed to determine facial features of a user. The method further comprises computing an emotional quotient of the user based on the facial features, determining a trigger to re-compute the sampling frequency the feed, based in part on the emotional quotient and computing a new sampling frequency based in part on the trigger. Thereafter, the method comprises generating instructions for the sensor to capture the feed at the new sampling frequency.

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Chennai, India

Arun Jeyaprasad Arjun Jeyarani