ANALYSIS AND DEEP LEARNING MODELING OF SENSOR-BASED OBJECT DETECTION DATA FOR ORGANIC MOTION DETERMINATION IN BOUNDED AQUATIC ENVIRONMENTS USING UNDERWATER POWERED SYSTEMS
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United States of America
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Apr 21, 2022
app pub date -
Oct 29, 2020
filing date -
Oct 29, 2020
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Abstract
Techniques for analysis and deep learning modeling of sensor-based object detection data for organic motion determination in bounded aquatic environments using underwater powered systems are described, including a light disposed substantially within a recess of a boundary wall, the light being disposed substantially underwater and configured to receive power using a conduit, and a spacer ring disposed circumferentially about an opening associated with the recess, the spacer ring being configured to secure the light within the recess and to provide a channel formed in the spacer ring, the channel being configured to receive the conduit.
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