Samsung Electronics Co., Ltd.

Barath Raj Kandur Raja

Vibhav Agarwal

Sreevatsa Dwaraka Bhamidipati

Vanraj Vala

Mohamed Akram Ulla Shariff

Sujay Srinivasa Murthy

Parameswaranath Vadackupurath Mani

Yashwant Singh Saini

Raju Suresh Dixit

Kumar Murugesan

Sanjay Ghosh

Mahender Rampelli

Amit Arvind Mankikar

Balabhaskar Veerannagari

Kachana Raghunatha Reddy

Arjun Raj Kumar S

Ankur Agarwal

Adarsha Ananda

Sourabh Vasant Gothe

Srinivasa Rao Siddi

Mritunjai Chandra

Himanshu Arora

Jayesh Rajkumar Vachhani

Beda Prakash Meher

Namitha Poojary

Ravi Bharathi Krishnan

Kavin Kumar Thangadorai

Hojun Jaygarl

Sriram Shashank

Sukumar Moharana

Sumit Kumar

Pilsik Choi

Periyasamy Paramasivam

Naresh Purre

Debi Prasanna Mohanty

Manoj Goyal

Srihari Sriram

Seungseok Kang

Hema Aravindan

Sridhar Rajiv Kavuri

Sri Lakshmi Punuru

Gopi Ramena

Shwetank Choudhary

Hallah Zorinsangi

Sanguk Jeon

Sharmila Mani

Hemant Tiwari

Wan Seok Kim

Phani Avadooth Rekapalli Veera Venkata

Ketki Aniruddha Gupte

Himanshi Sinha

Arko Sabui

Karthikeyan Subramani

Rishabh Kumar

Indira Preethi Jain Gargatti Ajith

Sudeep Kumar Kodali

Rishabh Khurana

Pranay Kashyap

Jaehoon Park

Shashank Sriram

Mrinaal Dogra

Aditi Anil Kagane

Ankita Bhardwaj

Aayush Yadav

Dwakara Bhamidipati Sreevatsa

Rakshith Srinivas

Likhith Amarvaj

Abhishek Kumar Bansal

Vipin Rao

Parmarth Vawa Sarathi Rai

Muthu Kumaran

Manjunath Bhimappa Ujjinakoppa

Mansoor Variyathapara Mohammed

Balaji Vijayanagaram Ramalingam

Dhruv Modi

Anup Kumar Kandhari

Sharath Venkataram Bangalore Shiva Kumar

Kamal Krishna

Raghavendra Kulkarni

Venkata Sreenath Yalamarthi

Ananya Padmanabha Suvarna

Phani Avadooth Veera Venkata Rekapalli

Jyothish Narayan

Magesh Krishnamurthy

Rajath Basur Kumaraswamy

Sushant Kathuria

Ragava Mysore Veera

Bharath C

Harshavardhana

Ishan Vaid

Kranti Chalamalasetti

Kalyan Kakani

Harshavardhana Poojari

Rakshith S

A method for generating at least one segment of a video by an electronic device is provided. The method includes identifying at least one of a context associated with the video and an interaction of a user in connection with the video, analyzing at least one parameter in at least one frame of the video with reference to at least one of the context and the interaction of the user, wherein the at least one parameter includes at least one of a subject, an environment, an action of the subject, and an object, determining the at least one frame in which a change in the at least one parameter occurs, and generating at least one segment of the video comprising the at least one frame in which the parameter changed as a temporal boundary of the at least one segment.

Method and electronic device for generating a segment of a video

A method of controlling a plurality of Internet of Things (IoT) devices included in an IoT ecosystem is provided. A change of a value of a resource of an IoT device from among the plurality of IoT devices is detected, an intent associated with the resource of which the value is changed is identified, a resource associated with the identified intent from among resources of the plurality of IoT devices is determined, and a value of the determined resource is controlled based on a context corresponding to the identified intent.

Method and systems for achieving collaboration between resources of IoT devices

Accordingly, embodiments herein disclose a method and apparatus for retrieving intelligent information from an electronic device (). The method includes receiving, by the electronic device (), an input from a user. Further, the method includes identifying, by the electronic device (), at least one data item to generate at least one metadata tag. Further, the method includes automatically generating, by the electronic device (), the at least one metadata tag related to the at least one data item based on a plurality of parameters. Further, the method includes providing, by the electronic device (), at least one priority to the at least one metadata tag. Further, the method includes storing, by the electronic device (), the at least one metadata tag at the electronic device ().

Method and apparatus for retrieving intelligent information from electronic device

Example systems and methods provide input suggestions to a user to improve user experience on user devices. The input suggestions can be fill information from another app on device to the present app being used by user, information for performing a search (without the user having to copy-paste data or entering the data manually), responses to a message/notification received by the user, information/content/data to be shared between apps (without switching between apps), and emojis/GIFs that can be used by the user. The method includes analyzing one or more content of one or more screen displayed on device, generating at least one of a logical tree structure and a data mashup model of the one or more analyzed content for each screen, and providing a recommendation to a user. The recommendation can be a connected action or an input suggestion.

Systems and methods for smart capture to provide input and action suggestions

Embodiments herein disclose methods and systems for identifying behavioural trends across users. The system includes electronic devices. The electronic devices include a behavioural recommendation controller. The behavioural recommendation controller is configured to: detect a first plurality of activities performed by a plurality of first users in relation with a plurality of contexts; recognize the first plurality of physical activities in relation with the plurality of contexts for the first user; recognize multiple activities performed using smart devices by the first user during each first physical activity in each context; and recognize a second plurality of physical activities performed by multiple concurrent second users during each context to refer current behavior or new behavior of the users.

Methods and electronic devices for behavior detection using Federated Learning preliminary class

Disclosed is a method for a social interaction by a robot device. The method includes receiving an input from a user, determining an emotional state of the user by mapping the received input with a set of emotions and dynamically interacting with the user based on the determined emotional state in response to the input. Dynamically interacting with the user includes generating contextual parameters based on the determined emotional state. The method includes determining an action in response to the received input based on the generated contextual parameters and performing the determined action. The method further includes receiving another input from the user in response to the performed action and dynamically updating the mapping of the received input with the set of emotions based on the other input for interacting with the user.

Method for dynamic interaction and electronic device thereof

Embodiments herein disclose a method and electronic device for predicting multi-modal drawings. The method includes: receiving, by the electronic device, at least one of a text input and strokes of a drawing and determining, by the electronic device, features associated with the text input and features associated with the strokes of the drawing. The method includes classifying, by the electronic device, the features associated with the text input and the features associated with the strokes of the drawing into one of a dominant feature and a non-dominant feature and performing, by the electronic device, early concatenation or late concatenation of the features based on the classification; classifying, by the electronic device, the strokes of the drawing based on the concatenation into a category using a deep neural network (DNN) model; and predicting, by the electronic device, primary drawings corresponding to the category.

Method and electronic device for predicting plurality of multi-modal drawings

Methods and systems for predicting keystrokes using a neural network analyzing cumulative effects of a plurality of factors impacting the typing behavior of a user. The factors may include typing pattern, previous keystrokes, specifics of keyboard used for typing, and contextual parameters pertaining to a device displaying the keyboard and the user. A plurality of features may be extracted and fused to obtain a plurality of feature vectors. The plurality of feature vectors can be optimized and processed by the neural network to identify known features and learn unknown features that are impacting the typing behavior. Thereby, the neural network predicts keystrokes using the known and unknown features.

Methods and systems for predicting keystrokes using a unified neural network

An electronic device for providing contextual recommendations and a method therefor are provided. The electronic device includes a memory storing instructions, and at least one processor configured to execute the instructions to obtain text including characters, identify, based on a language model, a domain corresponding to the text, identify a reference of the characters based on the domain, and perform, based on the reference, an action related to the domain.

Contextual recommendation

An electronic device and a method for predicting a response are provided. The electronic device includes a display and a processor configured to receive at least one message, identify at least one contextual category of the at least one message, predict at least one response for the at least one message from a language model based on the at least one contextual category, and control the display to display the at least one predicted response.

Method and electronic device for predicting a response from context with a language model

A method and apparatus for managing applications by an electronic device are provided. The method and apparatus include identifying, by a processor, a secondary application based on an application executed on the electronic device or content included in the application, displaying a representation corresponding to the secondary application on the electronic device, selecting the representation based on an input, and invoking the secondary application corresponding to the selected representation on the electronic device.

Electronic device and method for managing applications on an electronic device

A data sharing method and an electronic device thereof are provided. The method includes communicating with a second electronic device and determining common interest information between a first user of the first electronic device and a second user of the second electronic device, and retrieving and sharing application data associated with the common interest information, with the second electronic device.

Data sharing method and electronic device thereof

A method and an apparatus for automatically changing a shape of an electronic device are provided. The method includes identifying, by the electronic device, at least one event triggered in the electronic device; and changing, by the electronic device, the shape of the electronic device according to the at least one identified event.

Method and an electronic device for automatically changing shape based on an event

The method and system for sorting the phonebook contacts by finding the weight of contacts for each application based on contact incentives and sorting the applications by measuring the weight of the applications based on application incentives is provided. The contact incentives can be identified for each application and the method calculates weight of contacts for each application. The method identifies the application incentives, and calculates the weight of each application. Based on the weight of contacts and the weight of application, the method normalizes sorts the contacts in phonebook.

System and method for sorting phonebook contacts based on context weightage and incentives

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Bengaluru, India

Barath Raj Kandur Raja