Sightline Innovation Inc.

Other

Maithili Mavinkurve

Wallace Trenholm

Jason Cassidy

Mark Alexiuk

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.

System and method for specular surface inspection

There is provided systems and methods for laser scanning of one or more surfaces; in a particular embodiment, laser scanning of concrete. The system includes: at least one laser scanning module for acquiring imaging data comprising one or more distance measurements between the laser scanning module and each of the surfaces, according to a laser scanning modality; and a computing module, including one or more processors, in communication with the laser scanning module, for: aggregating the imaging data; processing and denoising the imaging data; and determining the presence or absence of a condition on each of the surfaces based on the imaging data.

System and method for integrated laser scanning and signal processing

An application provisioning system and method. A server provides an application provisioning service. A user of a client provides a schema defining an application. The application interacts with peripherals coupled to the client and receives input from sensors coupled to the peripherals. The sensor data is provided to the server for processing, including by neural networks. The application includes a workflow defining a finite state machine that traverses states at least partially based on the response to sensor data. The server may provide dynamic reallocation of compute resources to resolve demand for classifier training job requests; use of jurisdictional certificates to define data usage and sharing; and data fusion. Applications include manufacturing verification, medical diagnosis and treatment, genomics and viral detection.

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Markham, Canada

Maithili Mavinkurve