Wipro Limited

Genpact Luxembourg S.à R.l. II

Adrita Barari

Manjunath Ramachandra

Ghulam Mohiuddin Khan

Sethuraman Ulaganathan

Manjunath Ramachandra Iyer

Abhilash Nvs

Chirag Jain

Krishna Dev Oruganty

Amit Arora

Siva Tian

Prasanna Hegde

Nitish Kumar

Edmond Schneider

Vikram Mahidhar

A method and system are provided for assessing damage to a structure. According to one embodiment, the method includes using a classifier that is trained to associate respective portions of in an image of a structure with respective external parts of the structure to detect several of external parts of a structure in a first image of the structure. The method also includes using a first machine learning system, trained to perform segmentation of an image, to identify one or more image segments in a second image, where each image segment represents damage of a particular type and, using a second machine learning system, trained to associate image segments with external parts identified in an image, to associate a first image segment with a first external part, indicating damage to the first external part.

System and method for artificial intelligence based determination of damage to physical structures

A camera for generating distortion free images and a method thereof is disclosed. The camera includes a plurality of lenses, wherein each of the plurality of lenses has a dedicated sensor. The camera further includes a processor communicatively coupled to the plurality of lenses. The camera further includes a memory communicatively coupled to the processor and having instructions stored thereon, causing the processor, on execution to capture a plurality of images through the plurality of lenses and to generate a single distortion free image from the plurality of images based on a deep learning technique trained using a mapping of each of a plurality of sets of low resolution images generated in one or more environments to an associated distortion free image, wherein one or more low resolution images in each of the plurality of sets are distorted.

System and method for generating distortion free images

Disclosed subject matter relates to digital media including a method and system for generating a contextual audio related to an image. An audio generating system may determine scene-theme and viewer theme of scene in the image. Further, audio files matching scene-objects and the contextual data may be retrieved in real-time and relevant audio files from audio files may be identified based on relationship between scene-theme, scene-objects, viewer theme, contextual data and metadata of audio files. A contribution weightage may be assigned to the relevant and substitute audio files based on contextual data and may be correlated based on contribution weightage, thereby generating the contextual audio related to the image. The present disclosure provides a feature wherein the contextual audio generated for an image may provide a holistic audio effect in accordance with context of the image, thus recreating the audio that might have been present when the image was captured.

Method and system for generating a contextual audio related to an image

This disclosure relates generally to the text-to-speech synthesis and more particularly to a system and method for rendering textual messages using customized natural voice. In one embodiment, a system for rendering textual messages using customized natural voice, is disclosed, comprising a processor and a memory communicatively coupled to the processor. The memory stores processor instructions, which, on execution, causes the processor to receive present textual messages and at least one of previous textual messages, response to the previous textual messages or receiver's context. The processor further predicts final emotional state of sender's customized natural voice based on an intermediate emotional state and the receiver's context. The processor further synthesizes the sender's customized natural voice based on the predicted final emotional state of the sender's customized natural voice, voice samples and voice parameters associated with the at least one sender.

System and method for rendering textual messages using customized natural voice

The present disclosure relates to method and system for determining intent of subject using behavioural pattern by intent determination system. The intent determination system receiving video data associated with subject from one or more information sources, extracting pre-defined number of femes before target frame from video data of subject, obtaining plurality of behavioural parameters of subject for each of extracted frames, determining score for plurality of behavioural parameters of extracted femes using trained intent model, calculating weighted average score for plurality of behavioural parameters of extracted frames based on score of each of behavioural parameters, analysing emotion of subject for pre-defined number of frames based on weighted average score and determining intent of subject based on emotion of subject analysed. The present disclosure removes the need of human intervention in determining intent of subject.

Method and system for determining an intent of a subject using behavioural pattern

A testing device for performing testing across a plurality of smart devices is disclosed. The testing device may be configured to register the plurality of smart devices to be accessed for performing testing. At least one time-window at which each smart device is idle may be determined, by the testing device, for the plurality of smart devices. Upon gathering the testing criteria and time duration for performing a testing operation, the testing device may be configured to dynamically create a test group that includes one or more smart devices from the plurality of smart devices such that the one or more smart devices in the test group satisfy the testing criteria and the at least one time-window of smart devices in the test group is within the time duration.

Growing community of inventors

Kolkata, India

Adrita Barari