Michael Alan Greene

Address:

3337 Garnet Rd, Parkville, MD 21234

Phone:

(410)3404272

VIN:

5N1AN0NW8CC512476

Make:

NISSAN

Model:

XTERRA

Year:

2012

Address:

3337 Garnet Rd, Parkville, MD 21234

Phone:

(410)8702130

VIN:

5N1AN08U97C505651

Make:

NISSAN

Model:

XTERRA

Year:

2007

US Patent:

48901369, Dec 26, 1989

Filed:

May 16, 1988

Appl. No.:

7/194205

Inventors:

Michael Greene - Baltimore MD
Norman Michlin - Dearborn MI

Assignee:

Michlin Diazo Products - Dearborn MI

International Classification:

G03D 700
G03G 2730

US Classification:

355 27

Abstract:

A ventilation system for a diazo copy machine of the type having an exposure chamber containing a source of illumination for exposure of an original image onto diazo copy material and developer chamber utilizing ammonia vapors to develop the image on the diazo copying material. The ventilation apparatus comprises separate means for ventilating the exposure chamber and for ventilating the developing chamber. Inlet means are provided in the exposure chamber for admitting ambient air thereinto, and outlet means are provided for venting hot air from the exposure chamber into the ambient environment. Vacuum means are provided for exhausting ammonia-laden air from the developing chamber, and an absorber chamber is provided which is in fluid communication therewith, cartridge means being disposed within the absorber chamber for selectively absorbing ammonia fumes. Ammonia-laden fumes are drawn from the developing chamber into the absorber cartridge and then exhausted into the ambient environment.

US Patent:

20230014590, Jan 19, 2023

Filed:

Jul 16, 2021

Appl. No.:

17/378027

Inventors:

- Roseland NJ, US
Yair Pike - San Francisco CA, US
Harini Pundi Satyanarayanan - New York NY, US
Michael Greene - Seattle WA, US
Lauren Miller - New York NY, US

International Classification:

G06F 8/34
G06F 3/0482
G06F 3/0484
G06F 3/0481
G06F 40/274
G06F 3/0486

Abstract:

A method for providing a user interface in a low-code or no-code development platform includes generating, by a computing system, a graphic user interface of an application development program. The graphic user interface includes: a first area including a list of blocks; a second area including a structured data object comprising nodes corresponding to one or more of the blocks; and a third area including a parameter field of a selected one of the nodes, wherein the parameter field is configured to receive user input defining both a static string and a dynamic variable.

US Patent:

20210350189, Nov 11, 2021

Filed:

Jun 17, 2021

Appl. No.:

17/350764

Inventors:

- Mountain View CA, US
Michael Greene - San Francisco CA, US

International Classification:

G06K 9/62
G06F 16/387
G06K 9/46
G06T 7/11
G06T 7/70

Abstract:

A location of an object of interest () is determined using both observations and non-observations. Numerous images (-) are stored in a database in association with image capture information, including an image capture location (-). Image recognition is used to determine which of the images include the object of interest () and which of the images do not include the object of interest. For each of multiple candidate locations () within an area of the captured images, a likelihood value of the object of interest existing at the candidate location is calculated using the image capture information for images determined to include the object of interest and using the image capture information for images determined not to include the object of interest. The location of the object is determined using the likelihood values for the multiple candidate locations.

US Patent:

20200012903, Jan 9, 2020

Filed:

May 24, 2017

Appl. No.:

16/468196

Inventors:

- Mountain View CA, US
Michael Greene - San Francisco CA, US

Assignee:

Google LLC - Mountain View CA

International Classification:

G06K 9/62
G06K 9/46
G06F 16/387
G06T 7/70
G06T 7/11

Abstract:

A location of an object of interest () is determined using both observations and non-observations. Numerous images (-) are stored in a database in association with image capture information, including an image capture location (-). Image recognition is used to determine which of the images include the object of interest () and which of the images do not include the object of interest. For each of multiple candidate locations () within an area of the captured images, a likelihood value of the object of interest existing at the candidate location is calculated using the image capture information for images determined to include the object of interest and using the image capture information for images determined not to include the object of interest. The location of the object is determined using the likelihood values for the multiple candidate locations.

US Patent:

20180046910, Feb 15, 2018

Filed:

Aug 10, 2016

Appl. No.:

15/233414

Inventors:

- Mountain View CA, US
Michael Greene - San Francisco CA, US

International Classification:

G06N 3/08
G06N 5/02

Abstract:

The present disclosure provides systems and methods that use machine-learned models, such as deep neural networks, to predict and prevent adverse conditions at structural assets. One example method includes obtaining data descriptive of a plurality of images that depict at least a portion of a geographic area that contains a first structural asset. The plurality of images include at least a first image captured at a first time and a second image captured at a second time that is different than the first time. The method includes inputting data descriptive of at least the first image, the first time, the second image, and the second time into a condition prediction model. The method includes receiving, as an output of the condition prediction model, at least one prediction regarding the occurrence of an adverse condition at the first structural asset during one or more future time periods.