Samsung Electronics Co., Ltd.

Hl Klemove Corp.

Soul Vision Creations Private Limited

Shubham Jain

Sravanth Aluru

Gaurav Baid

Renju Chirakarotu Nair

Jatin Garg

Abhishek Gogia

Pranav Jadav

Nikhil Sahni

Sharmila Mani

Aditya Jhawar

Abhishek Verma

Vinuchackravarthy S

Prabhat Kumar

Shrey Chopra

Rakesh V

Umesh Murlidhar Patil

Balwant Singh Shekhawat

A device for graphical rendering includes a memory and processing circuitry. The processing circuitry is configured to receive sample values, transmitted by one or more servers, of samples of an object, wherein the sample values are generated by the one or more servers from inputting coordinates into a trained neural network and outputting, from the trained neural network, the sample values of the samples, store the sample values in the memory, and render image content of the object based on the sample values.

Real-time rendering of image content generated using implicit rendering

A method for securely sharing of data by an electronic device is provided. The method includes receiving, by the electronic device, data associated with the at least one application available at the electronic device and obtaining, by the electronic device, secured data by transforming the data associated with at least one application into an unrecognizable format using at least one conceal factor and at least one noise input. Further, the method includes extracting, by the electronic device, a plurality of features from the secured data, and sharing, by the electronic device, the plurality of features extracted from the secured data to a plurality of servers.

Method and electronic device for securely sharing of data

The present disclosure is related in general to field of machine learning and image processing, that provides a method and system for detecting and classifying lanes. A lane detection and classification system receives an input image from a data source and segments the input image into plurality of segments using a trained semantic segmentation model. Further, one or more lane markings are detected in the segmented image and, lane pattern and lane colour of each of the one or more lane markings, wherein each lane marking is associated with a priority. Subsequently, a binary image comprising lane markings of ego lanes of the host vehicle is generated and coefficient values of the ego lanes of the host vehicle are determined based on the priority value associated with the lane markings of the ego lanes and current position of the host vehicle, using a trained Convolutional Neural Network (CNN) model.

Method and system for detecting and classifying lanes

A method of traversing across multiple user interface layers in a hierarchy of an application by an electronic device is provided. The method includes displaying a first user interface layer of the application on a screen of an electronic device. Further, the method includes detecting an input on a first graphical element displayed within the first user interface layer, and displaying, on the screen, the first user interface layer, a second user interface layer of the application, and at least one first indicia indicating a relation between the first user interface layer and the second user interface layer based on the input to traverse to the second user interface layer.

Method and system for managing and displaying application

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Bengaluru, India

Shubham Jain