Abstract: The present disclosure provides a method for intelligent user localization in a metaverse, including: detecting movements of a wearable head gear configured to present virtual content to a user, and generating sensor data and visual data using an inertial sensor and a camera, respectively, mapping the visual data to a virtual world using an image associated with the visual data to localize the user in the virtual world; providing the visual data and the sensor data to a first Machine Learning (ML) model and a second ML model, respectively; extracting a plurality of key points from the visual data and distinguishing stable key points and dynamic key points; and removing visual impacts corresponding to the visual data having a relatively low weightage, and providing a relatively high weightage to the sensor data processed through the second ML model.

Abstract: A user is able to extract financial data, particularly tables, from a document. The table is stored and the user can compare the data in this table with data from similar tables from previous documents. The user can see how financial data has changed historically by looking only at financial tables from the same type of document, for example, only balance sheet tables from annual reports for a specific public company, over many years, and see how the values have changed or whether any new categories or types of data have been added or deleted. From the time series of financial data, the user can gain real intelligence into an entity's financial health.

Abstract: A user is able to extract financial data, particularly tables, from a document. The table is stored and the user can compare the data in this table with data from similar tables from previous documents. The user can see how financial data has changed historically by looking only at financial tables from the same type of document, for example, only balance sheet tables from annual reports for a specific public company, over many years, and see how the values have changed or whether any new categories or types of data have been added or deleted. From the time series of financial data, the user can gain real intelligence into an entity's financial health.

Abstract: A method for enhancing image quality using an electronic device is provided. The method includes receiving, by the electronic device, an image frame from a network, monitoring, by the electronic device, a network parameter of the network, determining, by the electronic device, a context of the electronic device, identifying, by the electronic device, a visual degradation in the image frame based on the monitored network parameter and the context of the electronic device, and modifying, by the electronic device, a visual quality factor of the image frame based on the visual degradation in the image frame for enhancing the image quality.

Abstract: Embodiments herein provide a method for authenticating wireless devices. The method includes generating, by a first wireless device, first biometric data of a user based on a user input. The method further includes determining, by the first wireless device, at least one standard parameter of a first wireless signal being generated by the first wireless device. The method further includes modifying, based on the first biometric data, the at least one standard parameter of the first wireless signal resulting in a second wireless signal. The method further includes transmitting, by the first wireless device to a second wireless device, the second wireless signal, based on a match between the at least one standard parameter of the second wireless signal and at least one reference parameter of a third wireless signal that has been pre-stored in the second wireless device.

Abstract: A user is able to extract financial data, particularly tables, from a document. The table is stored and the user can compare the data in this table with data from similar tables from previous documents. The user can see how financial data has changed historically by looking only at financial tables from the same type of document, for example, only balance sheet tables from annual reports for a specific public company, over many years, and see how the values have changed or whether any new categories or types of data have been added or deleted. From the time series of financial data, the user can gain real intelligence into an entity’s financial health.

Abstract: A user is able to extract financial data, particularly tables, from a document. The table is stored and the user can compare the data in this table with data from similar tables from previous documents. The user can see how financial data has changed historically by looking only at financial tables from the same type of document, for example, only balance sheet tables from annual reports for a specific public company, over many years, and see how the values have changed or whether any new categories or types of data have been added or deleted. From the time series of financial data, the user can gain real intelligence into an entity's financial health.

Abstract: A user is able to extract financial data, particularly tables, from a document. The table is stored and the user can compare the data in this table with data from similar tables from previous documents. The user can see how financial data has changed historically by looking only at financial tables from the same type of document, for example, only balance sheet tables from annual reports for a specific public company, over many years, and see how the values have changed or whether any new categories or types of data have been added or deleted. From the time series of financial data, the user can gain real intelligence into an entity's financial health.

Abstract: Method and system for emphasizing objects is disclosed. The method includes receiving input characters from a user of the electronic device and predicting one or more characters based on the input characters. Moreover, the method includes calculating a distance of each predicted character from a last input character. The method also includes calculating an emphasizing priority of each predicted character based on priority of each predicted character and the distance of each predicted character from the last input character. The method further includes emphasizing the predicted characters based on the emphasizing priority of the predicted characters.