公开(公告)号：US20220058285A1

公开(公告)日：2022-02-24

申请号：US17416912

申请日：2019-12-19

Applicant: Sightline Innovation Inc.

Inventor： Wallace Trenholm ,  Maithili Mavinkurve ,  Mark Alexiuk ,  Jason Haydaman

IPC: G06F21/62 ,  G06F16/27 ,  G06N20/00

Abstract: Systems and methods for a computer-implemented data trust are provided. A system for providing a data trust for a data asset includes a data trust domain. The data trust domain includes a parent node associated with a trustee. The trustee administers the data trust. The data trust domain also includes a plurality of data partner nodes. The data partner nodes include at least one data producer node associated with a data producer and at least one data consumer node associated with a data consumer. The nodes in the data trust domain are communicatively connected to each other via a network. The data trust is administered according to a set of governance rules. The set of governance rules is defined in a smart contract.

公开(公告)号：US20210081549A1

公开(公告)日：2021-03-18

申请号：US17018663

申请日：2020-09-11

Applicant: Sightline Innovation Inc.

Inventor： Wallace Trenholm ,  Maithili Mavinkurve ,  Mark Alexiuk ,  Jason Haydaman

IPC: G06F21/60 ,  G06F21/62 ,  G06F16/182 ,  G06N20/00

Abstract: Systems and methods for sharing data assets via a computer-implemented data trust are provided herein. The method includes creating, in response to a user input, a data trust domain. Creating the domain includes instantiating a private network. The network includes a plurality of domain nodes. The domain nodes include a data producer node and a data consumer node. The data asset is provided by the data producer node. The method also includes defining access rights for the data asset as between the data consumer node and the data producer node. The method also includes creating a data pathway object. The data pathway object specifies the access rights for the data asset. The flow of data within the data trust domain is controlled according to the data pathway object.

公开(公告)号：US11436428B2

公开(公告)日：2022-09-06

申请号：US15997966

申请日：2018-06-05

Applicant: SIGHTLINE INNOVATION INC.

Inventor： Wallace Trenholm ,  Mark Alexiuk ,  Hieu Dang ,  Siavash Malektaji ,  Kamal Darchinimaragheh

IPC: G06K9/62 ,  G06N20/00 ,  G06N20/10 ,  G06N5/02 ,  G06N7/00 ,  G06N3/12

Abstract: A method and system for increasing data quality of a dataset for semi-supervised machine learning analysis. The method includes: receiving known class label information for a portion of the data in the dataset; receiving clustering parameters from a user; determining a data cleanliness factor, and where the data cleanliness factor is below a predetermined cleanliness threshold: assigning data without class label information as a data point to a cluster using the clustering parameters, each cluster having a cluster class label associated with such cluster; and determining a measure of assignment, and where the measure of assignment for each data point is below a predetermined assignment threshold, receiving a class label for such data points, otherwise, assigning the respective cluster class label to each data point with the respective measure of assignment below the predetermined assignment threshold; and otherwise, outputting the dataset with associated class labels for machine learning analysis.

公开(公告)号：US10977814B2

公开(公告)日：2021-04-13

申请号：US16239637

申请日：2019-01-04

Applicant: SIGHTLINE INNOVATION INC.

Inventor： Wallace Trenholm ,  Maithili Mavinkurve ,  Mark Alexiuk ,  Jason Cassidy

IPC: G06K9/20 ,  G06K9/62 ,  G06T7/514 ,  G06T7/00 ,  G01B11/25 ,  G06T5/00 ,  G06T5/50 ,  H04N5/369 ,  H04N5/372

Abstract: Embodiments described herein relate to systems and methods for specular surface inspection, and particularly to systems and methods for surface inspection comprising inverse synthetic aperture imaging (“ISAI”) and specular surface geometry imaging (“SSGI”). Embodiments may allow an object under inspection, to be observed, imaged and processed while continuing to be in motion. Further, multiple optical input sources may be provided, such that the object does not have to be in full view of all optical sensors at once. Further, multi-stage surface inspection may be provided, wherein an object under inspection may be inspected at multiple stages of an inspection system, such as, for an automotive painting process, inspection at primer, inspection at paint, inspection at final assembly. SSGI imaging modules are also described for carrying out micro-deflectometry.

公开(公告)号：US10176588B2

公开(公告)日：2019-01-08

申请号：US15265161

申请日：2016-09-14

Applicant: SIGHTLINE INNOVATION INC.

Inventor： Wallace Trenholm ,  Maithili Mavinkurve ,  Mark Alexiuk ,  Jason Cassidy

IPC: G06K9/60 ,  G06T7/514 ,  G06T5/00 ,  G06T5/50 ,  G06T7/00 ,  H04N5/369 ,  H04N5/372

Abstract: Embodiments described herein relate to systems and methods for specular surface inspection, and particularly to systems and methods for surface inspection comprising inverse synthetic aperture imaging (“ISAI”) and specular surface geometry imaging (“SSGI”). Embodiments may allow an object under inspection, to be observed, imaged and processed while continuing to be in motion. Further, multiple optical input sources may be provided, such that the object does not have to be in full view of all optical sensors at once. Further, multi-stage surface inspection may be provided, wherein an object under inspection may be inspected at multiple stages of an inspection system, such as, for an automotive painting process, inspection at primer, inspection at paint, inspection at final assembly. SSGI imaging modules are also described for carrying out micro-deflectometry.

公开(公告)号：US11449757B2

公开(公告)日：2022-09-20

申请号：US16613843

申请日：2018-05-16

Applicant: SIGHTLINE INNOVATION INC.

Inventor： Wallace Trenholm ,  Mark Alexiuk ,  Hieu Dang ,  Siavash Malektaji ,  Kamal Darchinimaragheh

IPC: G06K9/00 ,  G06N3/08 ,  G06T7/11 ,  G06N20/20 ,  G06F17/18 ,  G06N3/04 ,  G06T7/00

Abstract: A system and method for non-destructive optical coherence tomography (OCT) is provided. The system includes: an input interface for receiving OCT data including at least a C-scan; a processing unit executable to detect a feature on a surface or subsurface of the object, trained using a training set and configured to: separate the C-scan into A-scans; using a neural network, successively analyze each A-scan to detect the presence of an A-scan feature associated with the object; separate the C-scan into B-scans; segment each of the B-scans to determine thresholds associated with the object; using a neural network, successively analyze each segmented B-scan to detect the presence of an B-scan feature associated with the object; convert the C-scan to one or more two-dimensional representations; and using a neural network, detect the presence of an C-scan feature associated with the object.