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公开(公告)号:US11507252B2
公开(公告)日:2022-11-22
申请号:US16997441
申请日:2020-08-19
Inventor: Ariel Beck , Chandra Suwandi Wijaya , Khai Jun Kek
IPC: G06F3/0482 , G06F3/04845 , G06K9/62 , G06N20/00
Abstract: A graphical user interface (GUI) for forming hierarchically arranged clusters of items and operating thereupon through an electronic device equipped with an input-device and a display-screen is provided. The GUI comprises a first area configured to display a graphical-tree representation having a plurality of hierarchical levels, each of said level corresponds to at least one cluster of content-items formed by execution of a machine-learning classifier over a plurality of input content items. A second area is configured to display a dataset corresponding to the content-items classified within the clusters. A third area is configured to display a plurality of types of content representations with respect to each selected cluster, said representations corresponding to content-items classified within the cluster.
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公开(公告)号:US11564634B2
公开(公告)日:2023-01-31
申请号:US16366939
申请日:2019-03-27
Inventor: Vasileios Vonikakis , Ariel Beck , Khai Jun Kek
IPC: A61B5/00 , A61B5/0205 , A61B5/11 , A61B5/117 , A61B5/024
Abstract: The present subject matter discloses a system(s) and a method(s) for determining a health state of an individual. According to an embodiment, a method comprises measuring, by a heart rate sensor, a heart rate of the individual during operation within the environment. The method further comprises outputting, by a pressure sensing platform, pressure data of the individual. Further, the method comprises outputting, by an image capturing device, image data of the individual. The method further comprises inferring, by a processing unit, an amount of fat of the individual in the image data. The method further comprises updating, by the processing unit, the amount of fat of the individual using the pressure data. The method further comprises controlling, by the processing unit, a threshold for determining the health state of the individual, using the amount of fat and the heart rate of the individual.
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公开(公告)号:US11521313B2
公开(公告)日:2022-12-06
申请号:US17173822
申请日:2021-02-11
Inventor: Ariel Beck , Chandra Suwandi Wijaya , Athul M. Mathew , Nway Nway Aung , Ramdas Krishnakumar , Zong Sheng Tang , Yao Zhou , Pradeep Rajagopalan , Yuya Sugasawa
Abstract: A method and system for checking data gathering conditions or image capturing conditions associated with images during AI based visual-inspection process. The method comprises generating a first representative (FR1) image for a first group of images and a second representative image (FR2) for a second group of images. A difference image data is generated between FR1 image and the FR2 image based on calculating difference between luminance values of pixels with same coordinate values. Thereafter, one or more of a plurality of white pixels or intensity-values are determined within the difference image based on acquiring difference image data formed of luminance difference-values of pixels. An index representing difference of data-capturing conditions across the FR1 image and the FR2 image is determined, said index having been determined at least based on the plurality of white pixels or intensity-values, for example, based on application of a plurality of AI or ML techniques.
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公开(公告)号:US10861144B1
公开(公告)日:2020-12-08
申请号:US16698493
申请日:2019-11-27
Inventor: Xibeijia Guan , Jeevan Kumar Guntammagari , Myo Htun , Ariel Beck , Myo Min Latt , Roy Eng Chye Lim
IPC: G06T5/50 , G06T3/20 , G06T3/00 , G06T5/00 , G06K9/62 , H04N5/247 , H04N5/225 , G06K9/00 , H04N5/232
Abstract: The present subject matter refers an image-processing method comprises receiving a first-image of an object captured by a range-imaging device at a first viewing location. The transforming the first-image into a second image of the object, said second image corresponding to an image captured based on range-imaging at a second viewing location with respect to the object. The gaps in the second-image are identified based on comparison with the first image, such that the identified gaps within the second image are complemented to result in a complemented second image.
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公开(公告)号:US11250356B2
公开(公告)日:2022-02-15
申请号:US16366963
申请日:2019-03-27
Inventor: Ariel Beck , Vasileios Vonikakis , Khai Jun Kek , Chandra Suwandi Wijaya
Abstract: The present disclosure relates to a method and system for apportioning tasks to person in an environment. The method comprises capturing a first-value indicating a sympathetic-nerve based activity and a second-value indicating a parasympathetic-nerve based activity for at least one person operating in an environment. Thereafter, a quantitative-relation is determined between the first and second values. At-least one task is assigned for execution by said person within the environment based on such quantitative relation.
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公开(公告)号:US11227157B1
公开(公告)日:2022-01-18
申请号:US17003287
申请日:2020-08-26
Inventor: Athul M. Mathew , Ariel Beck , Souksakhone Bounyong , Eng Chye Lim , Khai Jun Kek
IPC: G06K9/00
Abstract: A system for gaze direction detection is disclosed herein. The system comprises a face detection unit configured to detect face information from a captured image of a spectator, a head pose unit configured to detect a head pose angle based on the face information; an eye measurement unit configured to detect eye information of at-least one of a left eye or a right eye of the spectator based on the detected face information; an eye-gaze detection unit configured to estimate a gaze angle of the at-least one of the left eye or the right eye of the subject based on the eye information; a conditional gaze detection unit configured to calculate a resultant gaze angle based on the estimated gaze angles of the left eye and right eye and the head pose angle; and an effective gaze detection unit configured to estimate an effective gaze angle based the resultant gaze angle and head-pose angle.
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公开(公告)号:US20200305801A1
公开(公告)日:2020-10-01
申请号:US16366939
申请日:2019-03-27
Inventor: Vasileios VONIKAKIS , Ariel Beck , Khai Jun Kek
IPC: A61B5/00 , A61B5/0205 , A61B5/117 , A61B5/11
Abstract: The present subject matter discloses a system(s) and a method(s) for determining a health state of an individual. According to an embodiment, a method comprises measuring, by a heart rate sensor, a heart rate of the individual during operation within the environment. The method further comprises outputting, by a pressure sensing platform, pressure data of the individual. Further, the method comprises outputting, by an image capturing device, image data of the individual. The method further comprises inferring, by a processing unit, an amount of fat of the individual in the image data. The method further comprises updating, by the processing unit, the amount of fat of the individual using the pressure data. The method further comprises controlling, by the processing unit, a threshold for determining the health state of the individual, using the amount of fat and the heart rate of the individual.
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公开(公告)号:US12094180B2
公开(公告)日:2024-09-17
申请号:US17063923
申请日:2020-10-06
Inventor: Chandra Suwandi Wijaya , Ariel Beck
IPC: G06N20/00 , G06F11/34 , G06F18/214 , G06F18/231 , G06V10/25 , G06V10/40
CPC classification number: G06V10/25 , G06F11/3409 , G06F18/214 , G06F18/231 , G06N20/00 , G06V10/40
Abstract: The present subject matter refers a method for developing machine-learning (ML) based tool. The method comprises initializing an input dataset for undergoing ML based processing. The input dataset is pre-processed by a first model to harmonize features across the dataset. Thereafter, the dataset is annotated by a second model to define a labelled data set. A plurality of features are extracted with respect to the data set through a feature extractor. A selection of at-least a machine-learning classifier is received through an ML training module to operate upon the extracted features and classify the dataset with respect to one or more labels. A meta controller communicated with one or more of the first model, the second model, the feature extractor and the selected classifier for assessing a performance of at least one of first model and the feature extractor, a comparison of operation among the one or more selected classifier, and diagnosis of an unexpected operation with respect to one or more of the first model, the feature extractor and the selected classifier.
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9.
公开(公告)号:US20230111765A1
公开(公告)日:2023-04-13
申请号:US17500833
申请日:2021-10-13
Inventor: Zong Sheng Tang , Ariel Beck , Khai Jun Kek , Chandra Suwandi Wijaya
IPC: G06K9/62
Abstract: The present subject matter describes a method for labeling data in a computing system based on artificial intelligent techniques. The method comprises receiving input data and ordering the received input-data in a plurality of classes inferred based on at-least one of clustering and anomaly detection. The method further comprises receiving one more manual annotated labels for the ordered data. A first machine-learning (ML) model is trained with respect to the ordered data and thereby generating new labels. The performance of the first ML model is computed based on a comparison between the manual labels and the new labels. The labels are automatically propagated to unlabelled-portion of the ordered data based on execution of the first ML model based on accuracy of first ML model being above a predefined threshold.
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公开(公告)号:US11568318B2
公开(公告)日:2023-01-31
申请号:US17064692
申请日:2020-10-07
Inventor: Ariel Beck , Chandra Suwandi Wijaya
IPC: G06F8/34 , G06N20/00 , G06Q10/10 , G06Q10/06 , G06T7/00 , G06T7/30 , G06K9/62 , G06F16/245 , G06V10/40 , G06V10/22 , G09B19/16
Abstract: A method for developing machine-learning (ML) based tool including initializing an input dataset, which is pre-processed by a first model to harmonize the dataset. Historical data similar to the input data set is fetched from a historical database. Based thereupon a controller recommends a method and a control-setting associated with the identified model for the visual inspection process to a user. Thereafter, the dataset is annotated by a second model to define a labelled data set. A plurality of features are extracted with respect to the data set through a feature extractor. A machine-learning classifier operates upon the extracted features and classifies the dataset with respect to one or more labels. A meta controller communicates with one or more of the first model, the second model, the feature extractor and the selected classifier for assessing a performance of at least one of first model and the feature extractor.
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