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公开(公告)号:US20240193924A1
公开(公告)日:2024-06-13
申请号:US18581044
申请日:2024-02-19
Applicant: FUJITSU LIMITED
Inventor: Takashi KATOH , Kanata SUZUKI , Taro SUNAGAWA , Tomotake SASAKI
IPC: G06V10/778 , B25J9/16 , G06N3/04 , G06N3/094 , G06V10/764 , G06V10/774 , G06V10/776 , H04N23/61 , H04N23/695
CPC classification number: G06V10/778 , B25J9/1664 , G06N3/04 , G06N3/094 , G06V10/774 , G06V10/776 , H04N23/61 , H04N23/695 , G06V10/764
Abstract: A computer-readable storage medium storing a data collection program for causing a computer, which is configured to collect training data used for training a machine learning model, to perform processing. In an example, the processing includes: selecting a target data having a confidence level lower than a predetermined value, the confidence level corresponding to a confidence for an output from the machine learning model when collected data is input into the machine learning model; and collecting, for a target object related to the selected target data, the training data such that the confidence is high.
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公开(公告)号:US20240232231A1
公开(公告)日:2024-07-11
申请号:US18610415
申请日:2024-03-20
Applicant: Fujitsu Limited
Inventor: Kanata SUZUKI , Taro SUNAGAWA , Tomotake SASAKI , TAKASHI KATOH
IPC: G06F16/28
CPC classification number: G06F16/285
Abstract: A non-transitory computer-readable recording medium has stored therein a data gathering program executable by one or more computers, the data gathering program including: performing data augmentation on unlabeled data; providing a specification label to a group of augmented data pieces generated by the data augmentation, the specification label indicating that labels of the augmented data pieces all match; and providing, when a label for one data piece of the augmented data pieces is determined, the label to one or more data pieces each provided with a specification label that is same as a specification label of the one data piece.
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公开(公告)号:US20240104107A1
公开(公告)日:2024-03-28
申请号:US18223062
申请日:2023-07-18
Applicant: Fujitsu Limited
Inventor: Kanata SUZUKI , Yoshinobu IIMURA , Masatoshi OGAWA
IPC: G06F16/2458
CPC classification number: G06F16/2477
Abstract: A non-transitory computer-readable recording medium stores a program for causing a computer to execute a process, the process includes identifying, among pieces of feature information of a plurality of pieces of time-series data, a plurality of pieces of feature information similar to feature information of processing target time-series data, obtaining a predicted value distribution of the processing target time-series data based on each of the plurality of pieces of feature information, obtaining a combined distribution from the predicted value distribution, and determining a range of predicted value for the processing target time-series data based on the combined distribution.
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公开(公告)号:US20210326754A1
公开(公告)日:2021-10-21
申请号:US17213221
申请日:2021-03-26
Applicant: FUJITSU LIMITED
Inventor: Kanata SUZUKI , Yasuto YOKOTA
Abstract: A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process, the process includes identifying, among combinations of any two pieces of image data included in a plurality of pieces of image data that satisfies a first condition, similarity between two pieces of image data in a combination in which one image data satisfies a second condition in addition to the first condition; identifying, based on the calculated similarity between the two pieces of image data, a score that becomes greater as the similarity increases; and performing, by using training data based on another image data in the combination and the score, machine learning.
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公开(公告)号:US20240386277A1
公开(公告)日:2024-11-21
申请号:US18640007
申请日:2024-04-19
Applicant: Fujitsu Limited
Inventor: Kanata SUZUKI , Yoshinobu IIMURA , Masatoshi OGAWA
IPC: G06N3/092
Abstract: A recording medium stores a reinforcement learning program for causing a computer to execute a process. The process includes: calculating a second demand amount after a certain period of time and a reliability of the second demand amount based on a current first demand amount for a service provided in a predetermined environment; determining an action to be performed for the environment in accordance with a machine learning model based on input data that includes the second demand amount, the reliability, and a current first state of the environment; executing the determined action for the environment; and updating, based on a second state of the environment after the action is performed and a reward, a parameter of the model by constrained reinforcement learning in which the reward is increased in a range that satisfies a constraint on the state of the environment.
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公开(公告)号:US20240147030A1
公开(公告)日:2024-05-02
申请号:US18364089
申请日:2023-08-02
Applicant: Fujitsu Limited
Inventor: Takashi KATOH , Kanata SUZUKI
CPC classification number: H04N23/11 , H04N5/2624 , H04N23/69 , H04N23/80 , H04N23/698
Abstract: A control method including: obtaining an image of a given range captured by an image capturing device and a first invisible light image of the range captured by an invisible light image capturing device having a resolution lower than a resolution of the image capturing device; generating a second invisible light image at a resolution higher than a resolution of the first invisible light image by a machine learning model using the image and the first invisible light image as an input; identifying a target area from the range, based on an indicator indicating an uncertainty of each pixel in the second invisible light image; and obtaining, by an optical magnification control of the invisible light image capturing device, a third invisible light image of the target area at a resolution higher than a resolution of the target area in the first invisible light image.
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公开(公告)号:US20220143824A1
公开(公告)日:2022-05-12
申请号:US17513914
申请日:2021-10-29
Applicant: FUJITSU LIMITED
Inventor: Yasuto YOKOTA , Kanata SUZUKI
Abstract: A non-transitory computer-readable recording medium having stored therein an apparatus control program. The control program causes a computer to execute a process including, generating, by using a first machine learning model, based on first environmental information representing an operation environment of an apparatus at a first timing and first operation information representing an operation state of the apparatus at the first timing, second operation information, generating, by using a second machine learning model, based on second environmental information representing the operation environment of the apparatus at a second timing after the first timing and third operation information representing the operation state of the apparatus at the second timing, fourth operation information, controlling an operation of the apparatus based on the second operation information at a third timing after the second timing, and generating fifth operation information, by using the first machine learning model, by repeating as above.
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