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公开(公告)号：US20210295543A1
公开(公告)日：2021-09-23
申请号：US16827468
申请日：2020-03-23
Inventor： Xibeijia GUAN , Chandra Suwandi WIJAYA , Vasileios VONIKAKIS , Ariel BECK
Abstract: The present subject matter refers a method for training image-alignment procedures in a computing environment. The method comprises communicating one or more images of an object to a user and receiving a plurality of user-selected zones within said one or more through a user-interface. An augmented data-set is generated based on said one or more images comprising the user-selected zones, wherein such augmented data set comprises a plurality of additional images defining variants of said one or more communicated images. Thereafter, a machine-learning based image alignment is trained based on at-least one of the augmented data set and the communicated images.
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公开(公告)号：US20200240829A1
公开(公告)日：2020-07-30
申请号：US16257807
申请日：2019-01-25
Inventor： James Juzheng ZHANG , Vasileios VONIKAKIS , Ariel BECK , Chandra Suwandi WIJAYA
IPC: G01G19/414 , A47F9/04 , G06K9/00
Abstract: The present disclosure relates to smart weighing scale and methods related thereto. According to a method, at least one image corresponding to each of one or more grocery items resting on a pressure sensing platform of the smart weighing scale is captured. Further, at least a range profile and a range-azimuth signature corresponding to each of the one or more grocery items are obtained from a radar. Further, each of the one or more grocery items is automatically identified based on the at least one image, the range profile, and the range-azimuth signature corresponding to the said grocery item.
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公开(公告)号：US20250095134A1
公开(公告)日：2025-03-20
申请号：US18368443
申请日：2023-09-14
Inventor： Andre IVAN , Zong Sheng TANG , Ariel BECK
Abstract: The present disclosure discloses a method and system for visual inspection of a target product. The method includes a) receiving an image associated with the target product; generating a plurality of region of interests (ROIs) associated with the image; identifying, based on the plurality of non-terminal ROIs, a first set of features and a second set of features associated with the image. The first set of features and the second set of features are indicative of one of a presence of defect within the image or an absence of defect within the image. The method also includes determining, based on the first set of features and the second set of features, a result of the visual inspection of the target product associated with the image. The result is a success result or a failure result.
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公开(公告)号：US20240135689A1
公开(公告)日：2024-04-25
申请号：US17973177
申请日：2022-10-24
Inventor： Yuya SUGASAWA , Hisaji MURATA , Nway Nway AUNG , Ariel BECK , Zong Sheng TANG
IPC: G06V10/776
CPC classification number: G06V10/776
Abstract: According to an embodiment, a method for estimating robustness of a trained machine learning model is disclosed. The method comprises receiving a labelled dataset, a model of an object for which defect detection is required, and the trained machine learning model. Further, the method comprises determining one or more parameters associated with image capturing conditions in the environment. Furthermore, the method comprises performing an auto extraction of one or more defects using the model of the object and the labelled dataset based on image processing. Furthermore, the method comprises generating one or more images based on the one or more parameters and the one or more defects. Additionally, the method comprises testing the trained machine learning model using the generated images. Moreover, the method comprises estimating a robustness report for the machine learning model based on the testing of the machine learning model.
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Patent Agency Ranking
公开(公告)号：US20240020944A1
公开(公告)日：2024-01-18
申请号：US17867173
申请日：2022-07-18
Inventor： Ramdas KRISHNAKUMAR , Ariel BECK , Zong Sheng TANG , Khai Jun KEK , Satyam SATYAM , Masahiro ISHII , Yuto KITAGAWA
IPC: G06V10/72 , G06V10/762 , G06V10/764 , G06V10/74 , G06V10/98
CPC classification number: G06V10/72 , G06V10/762 , G06V10/764 , G06V10/761 , G06V10/993
Abstract: A method and system for sampling and augmenting a dataset associated with a first class and a second class, respectively, to balance the dataset of images is described. The method includes receiving a required number of reduced set of dataset images associated with the first class, creating a plurality of clusters from a set of images associated with the first class, and selecting a representative image from each cluster to provide a reduced set of images. Further, a median image and a non-defect artifact mask is generated corresponding to the set of images associated with the first class. Additionally, a defect foreground is extracted based on the median image and each defect image of another set of images associated with the second class. Finally, the at least one non-defect artifact is removed from the defect foreground to provide a new synthetic defect image for each defect image for augmentation.
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公开(公告)号：US20210294488A1
公开(公告)日：2021-09-23
申请号：US16824467
申请日：2020-03-19
Inventor： Vasileios VONIKAKIS , Yao ZHOU , Chandra Suwandi WIJAYA , Ariel BECK
IPC: G06F3/0484 , G06T7/00
Abstract: A method implemented in a computing-device with a display screen for image inspection. The method comprises displaying a distribution of a quality-indicia of at least one object in each of a plurality of images to be inspected, within a first area of the display screen. Within a second area of the display screen, a user-control is displayed to adjust a threshold-value with respect to an acceptance of at least one object in said plurality of images to be inspected. The threshold-value may be determined manually or automatically. A change in or update of threshold value is determined based on a user-operation performed over the user-control for adjusting the threshold value. Thereafter, a quality-indicia of at least one object in each the plurality of images is determined. Acceptable objects in respect of an image inspection procedure based on the updated threshold value and the determined quality-indicia are indicated.
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公开(公告)号：US20200311632A1
公开(公告)日：2020-10-01
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：US20190354777A1
公开(公告)日：2019-11-21
申请号：US15984963
申请日：2018-05-21
Inventor： Ariel BECK , Khai Jun Kek , Vasileios Vonikakis , Chandra Suwandi Wijaya
Abstract: There is provided a computer-implemented method for generating an output with respect to a group of individuals. The method includes: identifying the group of individuals amongst a plurality of individuals in an area being monitored by one or more sensors; determining, for each individual in the group of individuals, one or more individual-based features associated with the individual based on sensing data obtained from the one or more sensors; determining a group characteristic information associated with the group of individuals based on the one or more individual-based features determined for each individual in the group; and generating the output based on the group characteristic information determined for the group of individuals. There is also provide a corresponding system for generating an output with respect to a group of individuals.
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公开(公告)号：US20190239791A1
公开(公告)日：2019-08-08
申请号：US15888895
申请日：2018-02-05
Inventor： Ariel BECK , Jovia Jia Zhen LEE , Khai Jun KEK
CPC classification number: A61B5/165 , A61B3/112 , A61B5/02055 , A61B5/021 , A61B5/02405 , A61B5/053 , A61B5/0816 , A61B5/1116 , A61B5/1123 , A61B5/163 , A61B5/4803 , A61B5/7264 , G16H50/20
Abstract: The present invention relates to a system and method for monitoring and predicting the mental health of a person. Data is collected from multiple sensors including a camera and microphone. Additional sensors can be added to improve the robustness of the system such as heart rate sensors and respiration sensors. The data can be collected in phases that provide contextual awareness to the system. An algorithm can synchronize the data collected in the different phases and the data can be analyzed individually and collectively. Historical data can be included in the analysis to evaluate and predict the mental condition of a person.
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