Analysis and deep learning modeling of sensor-based object detection data in bounded aquatic environments

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United States of America

PATENT NO 12198473
APP PUB NO 20220122380A1
SERIAL NO

17534331

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Abstract

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Techniques for analysis and deep learning modeling of sensor-based object detection data in bounded aquatic environments are described, including capturing an image from a sensor disposed substantially above a waterline, the sensor being housed in a structure electrically coupled to a light housing, converting the image into data, the data being digitally encoded, evaluating the data to separate background data from foreground data, generating tracking data from the data after the background data is removed, the tracking data being evaluated to determine whether a head or a body are detected by comparing the tracking data to classifier data, tracking the head or the body relative to the waterline if the head or the body are detected in the tracking data, and determining a state associated with the head or the body.

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Patent Owner(s)

Patent OwnerAddress
GUARD INC112 DIVISADERO STREET SAN FRANCISCO CA 94117

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Barton, Chris San Francisco, US 23 200
Hubbard, Robin Nicholas San Francisco, US 12 381
Lau, Jonathan Chei-Feung San Francisco, US 4 13
Morris, Nigel Toronto, CA 25 183
Narasimhan, Srinivasa McDonald, US 16 30
Rouillac, Nichole Suzanne San Francisco, US 11 166

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