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公开(公告)号：US10318889B2
公开(公告)日：2019-06-11
申请号：US15633288
申请日：2017-06-26
Applicant: KONICA MINOLTA LABORATORY U.S.A., INC.
Inventor： Ting Xu
Abstract: A method for training a deep neural network (DNN) to perform a specified task with respect to images captured by a target camera, including: using an image captured by the target camera as a style target image, training a style transformer network to perform a style transformation that transforms any photorealistic input image into a transformed image that has contents of the input image, maintains photorealistic quality of the input image, and has a style that matches a style of the style target image; using the trained style transformer network to transform training image of an original training dataset into transformed training images; labeling the transformed training images with the training labels of the corresponding training image of the original training dataset, to form an augmented training dataset; and using the augmented training dataset to train the DNN to perform the specified task.
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Patent Agency Ranking
2.发明申请公开(公告)号：US20190101490A1
公开(公告)日：2019-04-04
申请号：US15720708
申请日：2017-09-29
Applicant: Konica Minolta Laboratory U.S.A., Inc.
Inventor： Leiming Wang , Ting Xu
IPC: G01N21/3504 , G01M3/38
Abstract: A gas concentration-length quantification method may include acquiring a first image including a gas plume with a camera; identifying and segmenting pixels corresponding to the gas plume in the first image; creating a mask image corresponding to the first image, where only pixels of the mask image corresponding to the gas plume in the first image have non-zero values; generating a background image corresponding to the first image using an image inpainting algorithm with the first image and the mask image as inputs; calculating a gas concentration-length for each pixel corresponding to the gas plume in the first image, based on the first image and the background image data; and triggering an alert when the gas concentration-length for at least one pixel exceeds a threshold level.
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3.发明申请公开(公告)号：US20190162657A1
公开(公告)日：2019-05-30
申请号：US16263576
申请日：2019-01-31
Applicant: Konica Minolta Laboratory U.S.A., Inc.
Inventor： Leiming Wang , Ting Xu
IPC: G01N21/3504 , G01M3/38
CPC classification number: G01N21/3504 , G01M3/38 , G01N2021/3509 , G01N2021/3531 , G06T7/0004 , G06T2207/10048 , G06T2207/30108
Abstract: A gas concentration-length quantification method, including: acquiring a first image including a gas plume with a camera; identifying and segmenting pixels corresponding to the gas plume in the first image; generating a background image corresponding to the first image using an image inpainting algorithm with the first image and positional information of the segmented pixels corresponding to the gas plume as inputs; calculating a gas concentration-length for each pixel corresponding to the gas plume in the first image, based on the first image and the background image data; and triggering an alert when the gas concentration-length for at least one pixel exceeds a threshold level.
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公开(公告)号：US10234380B1
公开(公告)日：2019-03-19
申请号：US15720708
申请日：2017-09-29
Applicant: Konica Minolta Laboratory U.S.A., Inc.
Inventor： Leiming Wang , Ting Xu
IPC: G01N21/3504 , G01M3/38
Abstract: A gas concentration-length quantification method may include acquiring a first image including a gas plume with a camera; identifying and segmenting pixels corresponding to the gas plume in the first image; creating a mask image corresponding to the first image, where only pixels of the mask image corresponding to the gas plume in the first image have non-zero values; generating a background image corresponding to the first image using an image inpainting algorithm with the first image and the mask image as inputs; calculating a gas concentration-length for each pixel corresponding to the gas plume in the first image, based on the first image and the background image data; and triggering an alert when the gas concentration-length for at least one pixel exceeds a threshold level.
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公开(公告)号：US10089556B1
公开(公告)日：2018-10-02
申请号：US15620492
申请日：2017-06-12
Applicant: KONICA MINOLTA LABORATORY U.S.A., INC.
Inventor： Ting Xu
Abstract: An artificial neural network for analyzing input data, the input data being a 3D tensor having D channels, such as D frames of a video snippet, to recognize an action therein, including: D spatial transformer modules, each generating first and second spatial transformations and corresponding first and second attention windows using only one of the D channels, and transforming first and second regions of each of the D channels corresponding to the first and second attention windows to generate first and second patch sequences; first and second CNNs, respectively processing a concatenation of the D first patch sequences and a concatenation of the D second patch sequences; and a classification network receiving a concatenation of the outputs of the first and second CNNs and the D sets of transformation parameters of the first transformation outputted by the D spatial transformer modules, to generate a predicted action class.
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公开(公告)号：US10359359B2
公开(公告)日：2019-07-23
申请号：US16263576
申请日：2019-01-31
Applicant: Konica Minolta Laboratory U.S.A., Inc.
Inventor： Leiming Wang , Ting Xu
IPC: G01N21/3504 , G01M3/38
Abstract: A gas concentration-length quantification method, including: acquiring a first image including a gas plume with a camera; identifying and segmenting pixels corresponding to the gas plume in the first image; generating a background image corresponding to the first image using an image inpainting algorithm with the first image and positional information of the segmented pixels corresponding to the gas plume as inputs; calculating a gas concentration-length for each pixel corresponding to the gas plume in the first image, based on the first image and the background image data; and triggering an alert when the gas concentration-length for at least one pixel exceeds a threshold level.
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