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US Patent 11450008 Segmentation using attention-weighted loss and discriminative feature learning

OverviewStructured DataIssuesContributors
Is a
Patent
Patent
0
Date Filed
February 27, 2020
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Date of Patent
September 20, 2022
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Patent Application Number
16803363
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Patent Citations
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US Patent 10929977 Coupled multi-task fully convolutional networks using multi-scale contextual information and hierarchical hyper-features for semantic image segmentation
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US Patent 10909349 Generation of synthetic image data using three-dimensional models
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US Patent 10007865 Learning method and learning device for adjusting parameters of CNN by using multi-scale feature maps and testing method and testing device using the same
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US Patent 10091386 Circuits for determining parameters for controlling an image sensor of an image capturing device and associated method
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US Patent 10169679 Learning method and learning device for adjusting parameters of CNN by using loss augmentation and testing method and testing device using the same
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US Patent 10275867 Utilizing a machine learning model to automatically visually validate a user interface for multiple platforms
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US Patent 10571454 Method of board lumber grading using deep learning techniques
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US Patent 10438082 Learning method, learning device for detecting ROI on the basis of bottom lines of obstacles and testing method, testing device using the same
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US Patent 10635927 Systems for performing semantic segmentation and methods thereof
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US Patent 10860836 Generation of synthetic image data for computer vision models
•••
Patent Inventor Names
Ambrish Tyagi
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Amit Kumar Agrawal
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Siddhartha Chandra
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Viveka Kulharia
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
11450008
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Patent Primary Examiner
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Mia M Thomas
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CPC Code
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G06T 7/194
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G06N 3/04
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G06F 17/18
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G06F 17/16
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G06T 11/20
0

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