Samsung Electronics Co., Ltd.

Nitesh Goyal

Sunil Rathour

Ankit Agarwal

Abhishek Jain

Vobbilisetty Sushant

Vipul Gupta

Rahul Agrawal

Dhananjay L Govekar

Nirmal Pandey

Deepak Kumar Garg

Vipin Khushu

Reetika Mittal

Ayush Chaturvedi

Mohit Chhabra

Govind Maheshwari

Manoj N Kumar

Amitoj Singh

Ankur Agrawal

Shashank Shekhar

Kalgesh Singh

Tasleem Arif

Prakhar Avasthi

Choice Choudhary

Saurabh Kumar

Munwar Khan

Abhinav Gaba

Rajan Dahiya

Pranav Jadav

Abhishek Gogia

Avinash Thakur

Harshit Oberoi

Nitin Kishorbhai Tanwar

Varad Arya

Pratush Kumar Srivastava

Yash Gupta

Ishani Ghosh

Sonam Chawla Bhatia

Gorav Sharma

Arun Goyal

Supriya Manna

Ekta Anil Pardeep Sachdev

Ridhima Jaiswal

Desh Deepak Agarwal

Anuj Mahajan

Aasheesh Nain

Jaideep Kumar Vishwakarma

Aman Jindal

Rohit Chaturvedi

A method for generating a virtual model of objects is provided. The method includes detecting, by a first electronic device, a communication session with a second electronic device, obtaining a first set of objects displayed on the first electronic device and a second set of objects displayed on the second electronic device based on the detection of the communication session, determining a first object from the first set of objects to be mapped to a second object from the second set of objects, predicting attributes of visible portions of the first object and the second object by mapping the first object to the second object, obtaining depth information related to the first object and the second object, and generating a virtual model of the first object and the second object based on the attributes of the visible portions of the first object and the second object and the depth information related to the first object and the second object.

Method and electronic device for generating partial virtual model of objects

A method for preventing data leakage may include: identifying data that is generated by at least one framework application in response to a data request from a first machine learning (ML) engine of a plurality of ML engines; creating a plurality of data blocks based on the generated data, a category of the first ML engine, and a tag associated with the first ML engine and the at least one framework application; determining whether the plurality of data blocks are valid to share with the first ML engine using an activity block chain associated with each of the plurality of framework applications; based on the plurality of data blocks being valid, sharing the plurality of data blocks with the first ML engine, and otherwise discarding the plurality of data blocks not to share with the first ML engine.

Method for preventing data leakage to machine learning engines available in electronic device

According to an embodiment, there is provided an electronic device comprising: a memory storing instructions; and at least one processor configured to execute the instructions to: generate state information regarding a device state of the electronic device of a first user and communication information regarding communications of the first user with a second user; transmitting the state information and the communication information to a server or an electronic device of the second user, wherein the state information and the communication information are used to determine communication availability of the first user and to provide the second user with information regarding the communication availability of the first user.

Method and apparatus for providing communication availability of users

A method for determining a proximity of at least one object using an electronic device is provided. The method includes obtaining hover data from a touch panel of the electronic device. Further, the method includes determining at least one of a first hover or a second hover based on the hover data of the at least one object obtained for the touch panel. Further, the method includes determining the proximity of the at least one object to the touch panel of the electronic device based on at least one of the first hover or the second hover.

Method for determining proximity of at least one object using electronic device

A method for accidental touch prediction using machine learning (ML) classification is provided. The method includes determining, by an electronic device, a mutual data index of a sensor data using a first ML model. Further, the method includes recognizing whether the sensor data corresponds to an object touch or a non-object touch based on the mutual data index. Further, the method includes performing, by the electronic device, one of detecting that the electronic device is in a pocket mode and providing an object touch notification on a touch screen of the electronic device in response to determining that the sensor data corresponds to the object touch, and recognizing whether the sensor data corresponds to an accidental touch or a non-accidental touch using at least one second ML model based on touch data in response to determining that the sensor data corresponds to the non-object touch.

Method and electronic device for accidental touch prediction using ml classification

An electronic device for controlling a brightness of a light source and an operating method of the electronic device are provided. According to the electronic device and the operating method, an image including an ambient environment of a light source is captured, information of an exposure of the captured image is obtained, information about a brightness of the ambient environment of the light source is determined based on the information about the exposure, and a brightness of the light source is controlled based on the determined information about the brightness of the ambient environment.

Electronic device and operating method of controlling brightness of light source

A method of battery management of an electronic device, the electronic device, and a non-transitory computer readable recording medium are provided. The method includes detecting, by the electronic device, that a battery management criterion is met, enabling at least one of a plurality of battery management functions, in response to detecting that the battery management criterion is met, and performing at least one action corresponding to the enabled at least one of the plurality of the battery management functions.

Method and electronic device for enabling at least one battery management function for managing battery usage

A method of processing an image in an electronic device. The method may comprise; obtaining a first image; selecting, based on comparing the first image with a plurality of second images, at least one third image from the plurality of second images, wherein the at least one third image is similar to the first image; identifying an identifier of an image group corresponding to the at least one third image; associating the first image with the identifier of the image group; and notifying, on the device, based on the identifier of the image group, existence of the at least one third image.

Method and system for management and operation over image in a computing system

A method of managing applications installed on a computing device and a computing device using the method are provided. The method includes identifying at least one application based on usage data of the computing device, fetching archive data and user data corresponding to the at least one application, creating backup data by correlating the archive data with the user data, and uninstalling the at least one application from the computing device once the creating of the backup data is completed.

Method of managing applications and computing device using the same

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Ghaziabad, India

Nitesh Goyal