Kyu Young Kim

20090123218, May 14, 2009

Nov 8, 2007

11/937295

Kyu Jin Kim - Fullerton CA, US

B43K 29/08
G06F 7/58

401195, 708250

A digital display pen includes an elongate body, a display provided on the body, a processor that generates alphanumeric data that is displayed on the display and a switch device that starts and/or stops operation of the display. The elongate body includes a writing tip that is adapted to leave a colored line on a paper. The display has four modes, time, minutes, world clock and random number. In the random number mode, one or more numbers for lottery is generated by the processor, and the generated number is displayed by the display. The number for lottery includes a Mega number, a roulette number or a Lotto number.

20210240739, Aug 5, 2021

Jan 31, 2020

16/779473

- Bentonville AR, US
Swagata Chakraborty - Santa Clara CA, US
Abhinandan Krishnan - Sunnyvale CA, US
Abon Chaudhuri - Sunnyvale CA, US
Aakash Mayur Mehta - San Francisco CA, US
Edison Mingtao Zhang - San Francisco CA, US
Kyu Bin Kim - Mountain View CA, US

Walmart Apollo, LLC - Bentonville AR

G06F 16/28
G06Q 30/06
G06N 3/04
G06F 16/2455
G06N 3/08

A method including obtaining image data and attribute information of a first item in an item catalog. The method also can include generating candidate variant items from the item catalog for the first item using a combination of (a) a k-nearest neighbors approach to search for first candidate variant items based on text embeddings for the attribute information of the first item, and (b) an elastic search approach to search for second candidate variant items based on image embeddings for the image data of the first item. The method additionally can include performing respective classifications based on respective pairs comprising the first item and each of the candidate variant items to filter the candidate variant items. The method further can include determining a respective distance between the first item and each of the candidate variant items, as filtered. The method additionally can include determining one or more items in the candidate variant items, as filtered, to include in a variant group for the first item, based on a decision function using a predetermined threshold and the respective distance for the each of the candidate variant items, as filtered. Other embodiments are described.

20210241076, Aug 5, 2021

Jan 31, 2020

16/779510

- Bentonville AR, US
Swagata Chakraborty - Santa Clara CA, US
Abhinandan Krishnan - Sunnyvale CA, US
Abon Chaudhuri - Sunnyvale CA, US
Aakash Mayur Mehta - San Francisco CA, US
Edison Mingtao Zhang - San Francisco CA, US
Kyu Bin Kim - Mountain View CA, US

Walmart Apollo, LLC - Bentonville AR

G06N 3/04
G06Q 30/06

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform obtaining a set of items that have been grouped together as matching items in a group; performing an ensemble mismatch detection; performing multiple detection models on the set of items to generate respective outputs regarding mismatches; combining the respective outputs to determine whether a quantity of detected mismatches is at least a predetermined threshold; when the quantity of detected mismatches is at least the predetermined threshold, the acts also can include separating at least one of the set of items from the group; and when the quantity of detected mismatches is not at least the predetermined threshold, the acts additionally can include maintaining each item of the set of items in the group. Other embodiments are disclosed.

20200099965, Mar 26, 2020

Sep 24, 2018

16/139430

- Houston TX, US
Kyu Han Kim - Palo Alto CA, US

H04N 21/235
H04N 21/2343
H04N 19/70
H04N 21/435
H04N 19/46

A system described herein provides real-time wireless video delivery using a multi-channel communications link. A method of employing elements of the system includes generating a first set of video data and generating a second set of video data. Further, encoding the first set of video data such that the second set of video data is a higher resolution version of the first set of video data and the encoded first set of video data is to supplement the second set of video data in response to a data drop.

20200092699, Mar 19, 2020

Nov 25, 2019

16/694324

- Houston TX, US
Kyu Han KIM - Palo Alto CA, US
Puneet JAIN - Palo Alto CA, US
Xiaochen LIU - Palo Alto CA, US

H04W 4/80
H04W 4/02

An example system comprising: a processing resource; and a memory resource storing machine readable instructions executable to cause the processing resource to: receive a Bluetooth Low Energy (BLE) signal transmitted from a user device; generate, from the BLE signal, a BLE moving pattern of the user device, wherein the BLE moving pattern is generated at a different entity than an entity that transmits the BLE signal; track an object carrying the user device via visual information of the object such that a visual moving pattern of the object is generated from the tracking; determine the visual moving pattern matches the BLE moving pattern; and assign, responsive to the determination, an identity obtained from the user device to the object being tracked via the visual information.

20190132696, May 2, 2019

Oct 27, 2017

15/796320

- Houston TX, US
Kyu Han Kim - Palo Alto CA, US
Puneet Jain - Palo Alto CA, US
Xiaochen Liu - Palo Alto CA, US

H04W 4/00
H04W 4/02

An example system comprising: a processing resource; and a memory resource storing machine readable instructions executable to cause the processing resource to: receive a Bluetooth Low Energy (BLE) signal transmitted from a user device; generate, from the BLE signal, a BLE moving pattern of the user device, wherein the BLE moving pattern is generated at a different entity than an entity that transmits the BLE signal; track an object carrying the user device via visual information of the object such that a visual moving pattern of the object is generated from the tracking; determine the visual moving pattern matches the BLE moving pattern; and assign, responsive to the determination, an identity obtained from the user device to the object being tracked via the visual information.

20180316928, Nov 1, 2018

Apr 28, 2017

15/582235

- Houston TX, US
Kyu Han KIM - Palo Alto CA, US

H04N 19/46
G06N 99/00
G06K 9/62
H04N 19/172
H04N 19/436

Examples provided herein describe a method for real-time processing of IoT data. For example, a first physical processor of an edge computing device may receive a set of data from a first IoT device communicably coupled to the edge device. The first physical processor may split the set of data into a set of individual data packets. A second physical processor of the edge device process the set of individual data packets by: concurrently applying, by a plurality of instances of the second physical processor of the edge computing device, a learning model to each of a corresponding plurality of data packets from the set of individual data packets; and annotating, by a subset of the plurality of instances of the second physical processor, a corresponding subset of the plurality of data packets with a corresponding output from the concurrent application of the learning model.

20170351345, Dec 7, 2017

Feb 27, 2015

15/535815

- HOUSTON TX, US
KYU HAN KIM - PALO ALTO CA, US
JEREMY GUMMESON - PALO ALTO CA, US
DAN GELB - PALO ALTO CA, US

G06F 3/0346
G06F 3/038
G06F 3/01
G06F 3/042

Examples relate to determining finger movements. In one example, a computing device may: receive input from at least one of: a first proximity sensor coupled to the frame at a first position and facing a first direction; or a second proximity sensor coupled to the frame at a second position and facing a second direction; determine, based on the input, that a finger action occurred, the finger action being one of: a first movement of a first finger, the first movement being detected by the first proximity sensor; a second movement of a second finger, the second movement being detected by the second proximity sensor; generate, based on the finger action, output that includes data defining an event that corresponds to the finger action; and provide the output to another computing device.