Han Song Kim

20130194265, Aug 1, 2013

Nov 16, 2012

13/678594

Wolfgang G Rehwald - Chapel Hill NC, US
Elizabeth R Jenista - Durham NC, US
Raymond J Kim - Chapel Hill NC, US
Han W Kim - Raleigh NC, US

G06T 15/08

345424, 345419

A virtual frequency selective inversion (VFSI) method receives at least one MR image representative dataset and an associated phase reference dataset, and classifies anatomical material into a first component representing anatomical material having a first range of resonance frequencies associated with a first range of phase differences between the MR image representative dataset and the associated phase reference image dataset, and a second component representing anatomical material having a second range of resonance frequencies associated with a second range of phase differences between the MR image representative dataset and the associated phase reference image dataset. The method assigns different visual attributes to first and second components derived using phase differences between the MR image representative dataset and the reference image dataset and displays an image.

58835288, Mar 16, 1999

Mar 20, 1997

8/822375

Abdul Qayyum Kashmiri - Fremont CA
Junaid Ahmed Ahmed - Milpitas CA
Han My Kim - Fremont CA

Cirrus Logic, Inc. - Fremont CA

H03K 190948

326 71

An input circuit to a semiconductor device may selectively accept different voltage logic levels (e. g. , TTL or CMOS) as selected by a preset selection signal. The selection signal activates an N-type or P-type transistor in the input circuit which alters the threshold switching voltage of the input circuit logic. By altering the input threshold voltage, both TTL and CMOS input signals may be correctly triggered. An additional circuitry may be provided to allow a low voltage circuit (e. g. , 3. 3 Volts) to be tolerant of higher voltage inputs (e. g. , 5 Volts). An isolation transistor isolates the input of the circuit from the high voltage signal, while a pulldown transistor pulls a high logic, high voltage signal down to supply voltage level.

20210271876, Sep 2, 2021

Apr 27, 2021

17/241791

- San Francisco CA, US
Han Suk Kim - San Francisco CA, US
James Kevin Murphy - San Francisco CA, US
Albert Yuen - San Francisco CA, US

G06K 9/00
G06K 9/62
G06K 9/46

The present disclosure relates to systems, methods, and non-transitory computer readable media for identifying traffic control features based on telemetry patterns within digital image representations of vehicle telemetry information. The disclosed systems can generate a digital image representation based on collected telemetry information to represent the frequency of different speed-location combinations for transportation vehicles passing through a traffic area. The disclosed systems can also apply a convolutional neural network to analyze the digital image representation and generate a predicted classification of a type of traffic control feature that corresponds to the digital image representation of vehicle telemetry information. The disclosed systems further train the convolutional neural network to determine traffic control features based on training data.

20200356773, Nov 12, 2020

May 9, 2019

16/408168

- San Francisco CA, US
Han Suk Kim - San Francisco CA, US
James Kevin Murphy - San Francisco CA, US
Albert Yuen - San Francisco CA, US

G06K 9/00
G06K 9/62
G06K 9/46

The present disclosure relates to systems, methods, and non-transitory computer readable media for identifying traffic control features based on telemetry patterns within digital image representations of vehicle telemetry information. The disclosed systems can generate a digital image representation based on collected telemetry information to represent the frequency of different speed-location combinations for transportation vehicles passing through a traffic area. The disclosed systems can also apply a convolutional neural network to analyze the digital image representation and generate a predicted classification of a type of traffic control feature that corresponds to the digital image representation of vehicle telemetry information. The disclosed systems further train the convolutional neural network to determine traffic control features based on training data.

20180222979, Aug 9, 2018

Nov 21, 2017

15/819153

- Redwood City CA, US
Han K. Kim - Redwood City CA, US
Louie Naumovski - Los Altos CA, US

C07K 16/28
A61K 45/06

The present disclosure provides antibodies and antibody drug conjugates that bind human CS1 and their uses to treat subjects diagnosed with a plasma cell neoplasm, for example, multiple myeloma.

20180112229, Apr 26, 2018

Dec 11, 2017

15/838142

- THOUSAND OAKS CA, US
Han Suk Kim - Pinole CA, US
David Van-Dinh Dang - Oak Park CA, US
Kenneth A. Feldmann - Newbury Park CA, US

C12N 15/82
C07K 14/415
C12Q 1/6895

Methods and materials for modulating low-nitrogen tolerance levels in plants are disclosed. For example, nucleic acids encoding low nitrogen tolerance-modulating polypeptides are disclosed as well as methods for using such nucleic acids to transform plant cells. Also disclosed are plants having increased low-nitrogen tolerance levels and plant products produced from plants having increased low-nitrogen tolerance levels.

20160122430, May 5, 2016

Oct 30, 2015

14/928738

- Redwood City CA, US
Han K. Kim - Redwood City CA, US
Louie Naumovski - Los Altos CA, US

C07K 16/28
A61K 45/06
A61K 47/48

The present disclosure provides antibodies and antibody drug conjugates that bind human CS1 and their uses to treat subjects diagnosed with a plasma cell neoplasm, for example, multiple myeloma.

20150077106, Mar 19, 2015

Nov 14, 2012

14/373895

Raymond J. Kim - Chapel Hill NC, US
Elizabeth R. Jenista - Durham NC, US
Han W. Kim - Raleigh NC, US

G01R 33/483
G01R 33/46
G01R 33/36
G06T 11/00

324309, 324318

Magnetic resonance imaging (MRI) acquisition and reconstruction techniques that invert MR signals of selected frequencies without the application of inversion RF pulses are disclosed. An example method comprises acquisition of at least one MR image representative dataset and an associated phase reference dataset, and classifies anatomical material into a first component representing anatomical material having a first range of resonance frequencies associated with a first range of phase differences between the MR image representative dataset and the reference image dataset and a second component representing anatomical material having a second range of resonance frequencies associated with a second range of phase differences between the MR image representative dataset and the reference image dataset. The method assigns different visual attributes to first and second components derived using phase differences between the MR image representative dataset and the reference image dataset and displays an image.