Praggya Garg

20090315998, Dec 24, 2009

Jun 20, 2008

12/214715

Praggya Garg - San Diego CA, US

H04N 17/04
H04N 17/00

348177, 348569

In accord with certain embodiments consistent with the present invention, a television diagnostic method involves providing a user selectable menu selection on the television display that invokes a diagnostic process; upon a user invoking the diagnostic process, carrying out a plurality of functional tests upon the television set; reading user settings from a memory in the television set; transmitting results from the plurality of tests to a diagnostic center via the Internet; and carrying out an interactive two-way communication with the diagnostic center to resolve any problems identified with the television set. This abstract is not to be considered limiting, since other embodiments may deviate from the features described in this abstract.

20100060117, Mar 11, 2010

Sep 6, 2008

12/205865

Praggya Garg - San Diego CA, US

SONY CORPORATION - Tokyo
SONY ELECTRONICS INC - Parkridge NJ

A47B 81/00

3122236

An apparatus comprising a connection hub having an input terminal for receiving a plurality of inputs from a plurality of component devices, and an output terminal for transferring a plurality of outputs from said connection hub to a display device. The apparatus further comprises a plurality of audio/video cables and a cable conduit coupled to the output terminal of the connection hub, wherein the audio/video cables traverse the cable conduit such that the visibility of the audio/video cables is obscured by the cable conduit.

20220374647, Nov 24, 2022

Sep 22, 2021

17/482290

- TOKYO, JP
PRAGGYA GARG - RANCHO SANTA FE CA, US

G06K 9/62
G06K 9/46
G06T 7/00
G06K 9/00
G06F 3/14
G06N 3/04
G06N 3/08

An electronic device and method for reverse image search is provided. The electronic device receives an image. The electronic device extracts, by a DNN model, a first set of image features associated with the image and generates a first feature vector based on the first set of image features. The electronic device extracts, by an image-feature detection model, a second set of image features associated with the image and generates a second feature vector based on the second set of image features. The electronic device generates a third feature vector based on combination of the first and second feature vectors. The electronic device determines a similarity metric between the third feature vector and a fourth feature vector of each of a set of pre-stored images and identifies a pre-stored image based on the similarity metric. The electronic device controls a display device to display information associated with the pre-stored image.

20220358327, Nov 10, 2022

Sep 30, 2021

17/490406

- Tokyo, JP
Praggya Garg - San Diego CA, US

Sony Group Corporation - Tokyo

G06K 9/62
G06K 9/46

Implementations generally relate to evaluation of similar content-based images. In some implementations, a method includes receiving a first image, where the first image includes at least one first object. The method further includes receiving a second image, where the second image includes at least one second object. The method further includes computing a structural similarity index measure (SSIM) value based on the at least one first object and the at least one second object. The method further includes computing a scale invariant feature transform (SIFT) value based on the at least one first object and the at least one second object. The method further includes computing a histogram value based on the at least one first object and the at least one second object. The method further includes computing a similarity score based on the SSIM value, the SIFT value, and the histogram value.

20210319596, Oct 14, 2021

Mar 9, 2021

17/196030

- Tokyo, JP
MOISES TAFOLLA - SAN DIEGO CA, US
PRAGGYA GARG - SAN DIEGO CA, US
ALLISON LANGLEY - SAN DIEGO CA, US
GARY LYONS - SAN DIEGO CA, US
ALEXANDER STONEHAM - SAN DIEGO CA, US
SEUNGHAN KIM - SAN DIEGO CA, US
LUIS VASCONCELOS - SAN DIEGO CA, US

G06T 11/00
G06F 3/0484

A system and method for node-based image colorization is provided. The system receives a first user input via a Graphical User Interface (GUI) of an image/video editing application and controls a display device to display a node graph on the GUI based on the first user input. The node graph includes an input node to select grayscale images and a colorization node which may represent a workflow for colorization of at least a first object in the grayscale images. The system receives a second user input associated with a setting of the colorization node and selects an image colorization model based on the second user input. The system executes the workflow associated with the colorization node to transmit the grayscale images to a computing device that hosts the selected image colorization model, and to receive colorized images including at least the first object colorized based on a color effect.