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公开(公告)号：US11341760B2
公开(公告)日：2022-05-24
申请号：US17007704
申请日：2020-08-31
Applicant: SAP SE
Inventor： Johannes Hoehne , Konrad Schenk
IPC: G06V30/413 , G06F40/166 , G06F40/205
Abstract: Disclosed herein are various embodiments for an augmented reality interaction, modeling, and annotation system. An embodiment operates by receiving an image including unknown data in an unknown format, including pixels. Each of the pixels is classified as one of a background pixel, a key pixel, or a value pixel representing the unknown data. For a plurality of the pixels classified as key pixels or value pixels, a plurality of locational data values associated with the unknown format are generated. Based on the locational data values, a key image and a corresponding value image from the received image are identified. The key image and the corresponding value image are output.
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Patent Agency Ranking
公开(公告)号：US11521274B2
公开(公告)日：2022-12-06
申请号：US16358850
申请日：2019-03-20
Applicant: SAP SE
Inventor： Steffen Vollmert , Luisa Karl , Konrad Schenk , Olga Cherepanova , Janet Dorothy Salmon , Ralf Ille , Thomas Zuerker
Abstract: The disclosure generally describes methods, software, and systems for estimating cost allocations, including a method for the following steps. Using a machine learning system, transactions are consolidated into estimated sender-receiver totals for costs transmitted by senders to receivers in an organization. A sender-receiver percentage matrix is determined from the estimated sender-receiver totals of a given sender and for each receiver of the transactions from the given sender. The sender-receiver percentage matrix includes, for each sender, estimated sender-receiver percentages. Current actual costs are determined for each sender to receivers for a given time period. Estimated cost allocations are determined for given time period using the sender-receiver percentage matrix. The estimated cost allocations are determined for each receiver in the organization based on a function of the current actual costs for each sender. A report that includes the estimated cost allocations is provided for presentation to a user.
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公开(公告)号：US11488107B2
公开(公告)日：2022-11-01
申请号：US16708000
申请日：2019-12-09
Applicant: SAP SE
Inventor： Luca Toldo , Konrad Schenk , Tunahan Atilgan , Martin Hoecker , Bettina Lieske , Ying Jiang
Abstract: In some embodiments, there is provided a system. The system may include at least one data processor and at least one memory storing instructions which, when executed by the at least one data processor, cause the apparatus to at least: determine, for a received document including at least one item, that the received document likely includes at least one missing item, the determination based on at least a machine learning model and the at least one item; and provide an indication of the at least one missing item. Related systems and articles of manufacture are also provided.
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公开(公告)号：US20220092405A1
公开(公告)日：2022-03-24
申请号：US17025845
申请日：2020-09-18
Applicant: SAP SE
Inventor： Matthias Frank , Hoang-Vu Nguyen , Stefan Klaus Baur , Alexey Streltsov , Jasmin Mankad , Cordula Guder , Konrad Schenk , Philipp Lukas Jamscikov , Rohit Kumar Gupta
Abstract: In an example embodiment, a deep neural network may be utilized to determine matches between candidate pairs of entities, as well as confidence scores that reflect how certain the deep neural network is about the corresponding match. The deep neural network is also able to find these matches without requiring domain knowledge that would be required if features for a machine-learned model were handcrafted, which is a drawback of prior art machine-learned models used to match entities in multiple tables. Thus, the deep neural network improves on the functioning of prior art machine learned models designed to perform the same tasks. Specifically, the deep neural network learns the relationships of tabular fields and the patterns that define a match from historical data alone, making this approach generic and applicable independent of the context.
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公开(公告)号：US20210174297A1
公开(公告)日：2021-06-10
申请号：US16708000
申请日：2019-12-09
Applicant: SAP SE
Inventor： Luca Toldo , Konrad Schenk , Tunahan Atilgan , Martin Hoecker , Bettina Lieske , Ying Jiang
Abstract: In some embodiments, there is provided a system. The system may include at least one data processor and at least one memory storing instructions which, when executed by the at least one data processor, cause the apparatus to at least: determine, for a received document including at least one item, that the received document likely includes at least one missing item, the determination based on at least a machine learning model and the at least one item; and provide an indication of the at least one missing item. Related systems and articles of manufacture are also provided.
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公开(公告)号：US20200302550A1
公开(公告)日：2020-09-24
申请号：US16358850
申请日：2019-03-20
Applicant: SAP SE
Inventor： Steffen Vollmert , Luisa Karl , Konrad Schenk , Olga Cherepanova , Janet Dorothy Salmon , Ralf Ille , Thomas Zuerker
Abstract: The disclosure generally describes methods, software, and systems for estimating cost allocations, including a method for the following steps. Using a machine learning system, transactions are consolidated into estimated sender-receiver totals for costs transmitted by senders to receivers in an organization. A sender-receiver percentage matrix is determined from the estimated sender-receiver totals of a given sender and for each receiver of the transactions from the given sender. The sender-receiver percentage matrix includes, for each sender, estimated sender-receiver percentages. Current actual costs are determined for each sender to receivers for a given time period. Estimated cost allocations are determined for given time period using the sender-receiver percentage matrix. The estimated cost allocations are determined for each receiver in the organization based on a function of the current actual costs for each sender. A report that includes the estimated cost allocations is provided for presentation to a user.
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