Insurance Services Office, Inc.

Matthew David Frei

Bryce Zachary Porter

Dean Lebaron

Caroline McKee

Kelly Redd

Samuel Warren

Sam Warren

Nicholas Sykes

Jared Dearth

Ravi Shankar

Vahid Meimand

Nick Sykes

Computer vision systems and methods for hazard detection from digital images and videos are provided. The system obtains media content indicative of an asset, preprocesses the media content, and extracts, based at least in part on one or more feature extractors, features from the preprocessed media content. The system determines, based at least in part on one or more classifiers, a value associated with a hazard, which can indicate the likelihood of a media content having the hazard. The system determines that the media content includes the hazard based at least in part on a comparison of the value to a threshold value. The system can generate a visual indication in the image indicative of the hazard.

Computer vision systems and methods for hazard detection from digital images and videos

Systems and methods for automatically detecting, classifying, and processing objects captured in an images or videos are provided. In one embodiment, the system receives an image from an image source and detects one or more objects in the image. The system performs a high-level classification of the one or more objects in the image. The system performs a specific classification of the one or more objects, determines a price of the one or more objects, and generates a pricing report comprising a price of the one or more objects. In another embodiment, the system captures at least one image or video frame and classifies an object present in the image or video frame using a neural network. The system adds the classified object and an assigned object code to an inventory and processes the inventory to assign the classified object a price.

Computer vision systems and methods for automatically detecting, classifying, and pricing objects captured in images or videos

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Lehi, UT, United States of America

Matthew David Frei