Gustavo K Rohde

US Patent:

20080107268, May 8, 2008

Filed:

Sep 10, 2007

Appl. No.:

11/853012

Inventors:

Gustavo Rohde - Pittsburgh PA, US
Jonathan Nichols - Crofton MD, US
Frank Bucholtz - Crofton MD, US

International Classification:

H04L 9/06

US Classification:

380263000

Abstract:

A system and method for encoding zero and one bits for transmission, including generating a first signal from a non-linear chaotic system to represent the one bit, with the signal's embedded vectors being within the non-linear system's attractor set, and generating a second signal from the non-linear system to represent the zero bit, with the signal's embedded vectors being outside the non-linear system's attractor set. The second signal encoding the zero bit can be generated by adding together two chaotic signals arising from the non-linear system initialized with different initial conditions, and weighting the second signal to have approximately the same energy as the first signal. One suitable chaotic systems is a Lorenz system. Systems and methods for decoding a transmitted stream of signals compare a detection statistic of the received stream of signals to a threshold value that depends on the chaotic system.

US Patent:

20210281361, Sep 9, 2021

Filed:

Jun 18, 2020

Appl. No.:

16/905842

Inventors:

- Washington DC, US
Jonathan M. Nichols - Crofton MD, US
Gustavo K. Rohde - Crozet VA, US
Nicole Menkart - Potomac MD, US
Geoffrey A. Cranch - Fairfax Station VA, US

International Classification:

H04L 1/06

Abstract:

Methods, apparatuses, and systems for calculating time delays by a Wasserstein approach are provided. A plurality of signals are recorded by a plurality of sensors (three or more), respectively, and received at a controller. The plurality of signals recorded by the plurality of sensors are generated in response to a signal emitted by a source. The plurality of signals are converted into a plurality of probability density functions. A cumulative distribution transform for each of the plurality of probability density functions is calculated. A time delay for each unique pair of the plurality of sensors is calculated by minimizing a Wasserstein distance between two cumulative distribution transforms corresponding to the unique pair of the plurality of sensors

US Patent:

20210093231, Apr 1, 2021

Filed:

Jan 22, 2019

Appl. No.:

15/733244

Inventors:

- Charlottesville VA, US
Mark MCDONALD - Charlottesville VA, US
Andrew M. SOUTHERLAND - Charlottesville VA, US
Gustavo ROHDE - Crozet VA, US
Yan ZHUANG - Charlottesville VA, US

International Classification:

A61B 5/11
A61B 5/00
G06K 9/00
G06N 20/00
G06F 3/01

Abstract:

The disclosed embodiments provide systems and methods for predicting presence of one or more neurological deficits. The system may include a microphone, a camera, one or more memory devices storing instructions, and one or more processors configured to execute the instructions to extract audio information including a period density entropy coefficient and a mel frequency cepstral coefficient from an audio feed received from the microphone. Additionally, the instructions may cause the processor to determine position and depth information of eye movement from a video feed received from the camera and detect features of interest including facial landmarks, spatial orientation of limbs, and positional information of limb movements from the video feed. The one or more processors may further extract the features of interest from the video feed and process the extracted features of interest by aligning the extracted features of interest to a common reference.

US Patent:

20190266869, Aug 29, 2019

Filed:

May 14, 2019

Appl. No.:

16/411353

Inventors:

- Pittsburgh PA, US
Gustavo K. Rohde - Pittsburgh PA, US
Frederick Lanni - Pittsburgh PA, US
Stephen C. Davis - Allison Park PA, US

Assignee:

Smoke Detective, LLC - Pittsburgh PA

International Classification:

G08B 17/12
G06K 9/00
H04N 7/18
G06K 9/62

Abstract:

Image-based fire detection methods are provided which include analyzing a field of view based on a plurality of images, determining if changes occur, and analyzing whether any such changes are due to smoke-like material. Changes due to large objects are ruled out, and drift in the scene or shaking of the image collection device is accounted for by the method. The methods employ representing images of the field of view with quantifiable values and comparing to thresholds established for each event, and activating an alarm if changes due to smoke-like material are detected. The fire detection methods may also include monitoring a field of view for changes, and only performing the analysis on the images if changes are detected. The monitoring and validating stages of the methods include collecting images at different sampling rates for different amounts of information.

US Patent:

20160307424, Oct 20, 2016

Filed:

Jun 28, 2016

Appl. No.:

15/194878

Inventors:

- Pittsburgh PA, US
Gustavo K. Rohde - Pittsburgh PA, US
Frederick Lanni - Pittsburgh PA, US

Assignee:

Smoke Detective, LLC - Pittsburgh PA

International Classification:

G08B 17/12
G06K 9/62
H04N 7/18

Abstract:

Image-based fire detection methods are provided which include analyzing a field of view based on a plurality of images, determining if changes occur, and analyzing whether any such changes are due to smoke-like material. Changes due to large objects are ruled out, and drift in the scene or shaking of the image collection device is accounted for by the method. The methods employ representing images of the field of view with quantifiable values and comparing to thresholds established for each event, and activating an alarm if changes due to smoke-like material are detected. The fire detection methods may also include monitoring a field of view for changes, and only performing the analysis on the images if changes are detected. The monitoring and validating stages of the methods include collecting images at different sampling rates for different amounts of information.

US Patent:

20160247375, Aug 25, 2016

Filed:

Feb 19, 2015

Appl. No.:

14/625689

Inventors:

Russell P. Mills - Coraopolis PA, US
Gustavo K. Rohde - Pittsburgh PA, US
Frederick Lanni - Pittsburgh PA, US

International Classification:

G08B 17/12
G06K 9/46
H04N 7/18

Abstract:

A fire detection device is provided that has a camera that captures a reference image and a measured image. A processor compares intensity of the measured image to intensity of the reference image and uses this comparison to determine if an alarm is generated to indicate the presence of fire. The intensity of the measured image may be the total number of photons of the measured image, and the intensity of the reference image may be the total number of photons of the reference image. In other arrangements, the intensity may be measured between individual corresponding pixels of the reference and measured images.

US Patent:

20140297648, Oct 2, 2014

Filed:

Sep 26, 2012

Appl. No.:

14/347498

Inventors:

- Pittsburgh PA, US
Dejan Slepcev - Pittsburgh PA, US
Gustavo Kunde Rohde - Pittsburgh PA, US

International Classification:

G06F 17/30

US Classification:

707740, 707758

Abstract:

A method performed by one or more processors includes retrieving a set of images; selecting, based on the images retrieved, a reference template; calculating optimal transportation plans between the reference template and each of the images in the set; and calculating, using the optimal transportation plans, a linear optimal transportation metric between at least two images in the set.

US Patent:

20140286562, Sep 25, 2014

Filed:

Sep 27, 2012

Appl. No.:

14/348342

Inventors:

- Pittsburgh PA, US
Gustavo Kunde Rohde - Pittsburgh PA, US
John A. Ozolek - Pittsburgh PA, US
Wei Wang - Pittsburgh PA, US

International Classification:

G06K 9/00

US Classification:

382133

Abstract:

A method performed by one or more processors, includes: receiving an image to be segmented into one or more representations of one or more biological structures; accessing data representing a set of biological structures that are derived from other biological structures delineated in a training image, wherein the training image is associated with a level of modality that corresponds to a level of modality associated with the image to be segmented; computing a normalized cross correlation of the received image against one or more of the biological structures in the set of biological structures; generating, based on computing, seed data representing an estimate of a spatial organization of the one or more biological structures in the received image; and segmenting, based on a normalized cross correction of the received image to the seed data, the received image into the one or more representations of the one or more biological structures.