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US Patent 10936907 Training a deep learning system for maritime applications

Patent 10936907 was granted and assigned to Buffalo Automation on March, 2021 by the United States Patent and Trademark Office.

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Contents

Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Applicant
Buffalo Automation
Buffalo Automation
Current Assignee
Buffalo Automation
Buffalo Automation
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10936907
Date of Patent
March 2, 2021
Patent Application Number
16537706
Date Filed
August 12, 2019
Patent Citations
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US Patent 10019907 Unmanned aerial vehicle obstacle detection and avoidance
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US Patent 10007269 Collision-avoidance system for autonomous-capable vehicle
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US Patent 10019002 Unmanned vehicle control and operation in a marine environment
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US Patent 10062010 System for building a map and subsequent localization
Patent Citations Received
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US Patent 11974069 Image processing method and device using feature map compression
9
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US Patent 11956569 Image processing method and device using a line-wise operation
10
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US Patent 11962937 Method and device of super resolution using feature map compression
11
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US Patent 11968472 Image pipeline processing method and device
12
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US Patent 11748887 Segmentation using an unsupervised neural network training technique
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US Patent 11412175 Super-resolution method and device using linewise operation
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US Patent 11908189 System and method for bandwidth reduction and communication of visual events
14
Patent Primary Examiner
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Oneal R Mistry
Patent abstract

An object detection network can be trained with training images to identify and classify objects in images from a sensor system disposed on a maritime vessel. The objects in the images can be identified, classified, and heat maps can be generated. Instructions can be sent regarding operation of the maritime vessel. For some training images, water conditions, sky conditions, and/or light conditions in the image can be changed to generate a second image.

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