Wipro Limited

Sibsambhu Kar

Manjunath Ramachandra Iyer

Vinutha Bangalore Narayanamurthy

Narendra Narasimha Rao

Sriram Chaudhury

Vinutha Bangalore Narayanmurthy

Ankit Kumar Singh

A method and a system of selective encryption of a test dataset is disclosed. In an embodiment, the method may include determining a relevancy grade associated with each of a plurality of datapoints within a test dataset by comparing the test dataset with a common heat map, wherein the common heat map is generated using a plurality of training datasets. The method may further include calculating, based on the relevancy grade, an encryption level associated with each of the plurality of datapoints. The method may further include selectively encrypting at least one datapoint from the plurality of datapoints based on the encryption level associated with each of the plurality of datapoints. The at least one data point is rendered to a user after being decrypted.

Method and system for selectively encrypting dataset

This disclosure relates to method and system for providing explanation for output generated by artificial intelligence (AI) model. The method may include receiving encrypted input data and a public encryption key from a client device, wherein the encrypted input data is encrypted using the public encryption key. The method may further include generating an encrypted AI model by encrypting an AI model using the public encryption key. The method may further include generating an encrypted output and an encrypted feature data based on the encrypted input data using the encrypted AI model, and generating an encrypted explanation for the encrypted output based on the encrypted feature data. The method may further include providing the encrypted output and the encrypted explanation to the client device for rendering, wherein the encrypted output and the encrypted explanation are decrypted by the client device using a private encryption key.

Method and system for providing explanation for output generated by an artificial intelligence model

The present disclosure relate to effectively determining spatial and temporal features for extracting low-level and high-level features from image frames of a multimedia content. A plurality of image frames are received from an imaging unit. Spatial filters are applied on each image frame to generate a first set of activation maps which provide spatial features in the image frames. Further, a temporal filter is applied on the plurality of image frames at a plurality of levels to generate one or more second set of activation maps corresponding to each level for determining temporal features in the image frames. Thereafter, the spatial feature from each image and temporal feature of the plurality of image frames from each level is extracted, which represent low-level and high-level spatial and temporal features.

Method and system for generating a text summary for a multimedia content

A method and a system of determining a relation between two or more entities in a text document is disclosed. In an embodiment, the method may include receiving training text data annotated with two or more entities, and creating one or more n-grams based on the training text data. The method may further include generating a Convolutional Neural Network (CNN) model using the one or more n-grams, and creating an entity vector using at least one of a word embedding and a numeric embedding based on the training text data. The method may further include generating a relation-entity model using the CNN model and the entity vector.

Method and device for determining a relation between two or more entities

A method and a system for controlling devices through voice interaction are disclosed. In an embodiment, the method may include identifying at least one feature of a target device and an action to be performed on the at least one feature, based on an intent and an object determined from a voice input received from a user. The method may further include determining a correspondence between the at least one feature and the action to be performed using a trained neural network. The method may further include comparing a current operational state of the at least one feature with an operational threshold of the at least one feature. The method may further include performing the action on the at least one feature based on the determined correspondence, when the current operational state is within limits of the operational threshold.

System and method for controlling devices through voice interaction

The present invention relates to the field of dynamic content creation and management and more particularly to dynamically create and insert immersive promotional content in a multimedia. The multimedia requested by a user is procured from a media server () and the one or more objects present in the multimedia is determined. The content of the multimedia is analyzed, and a decision is taken to immerse the promotional content in the multimedia based on the analysis of the multimedia. Further, a promotional content is created in real time using the components present in the asset database () based on the personalized user profile. The created promotional content is overlaid and blended with a at least one object from the one or more objects in the multimedia. The created promotional content and the multimedia is joined to form a composite media and is streamed to the user device.

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Bengaluru, India

Sibsambhu Kar