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US Patent 11450008 Segmentation using attention-weighted loss and discriminative feature learning
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Patent
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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
US Patent 10929977 Coupled multi-task fully convolutional networks using multi-scale contextual information and hierarchical hyper-features for semantic image segmentation
US Patent 10909349 Generation of synthetic image data using three-dimensional models
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
US Patent 10091386 Circuits for determining parameters for controlling an image sensor of an image capturing device and associated method
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
US Patent 10275867 Utilizing a machine learning model to automatically visually validate a user interface for multiple platforms
US Patent 10571454 Method of board lumber grading using deep learning techniques
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
US Patent 10635927 Systems for performing semantic segmentation and methods thereof
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
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Patent Number
11450008
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Patent Primary Examiner
Mia M Thomas
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CPC Code
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
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