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1. 发明公开

EP4455948A1 COMPUTER-IMPLEMENTIERTES VERFAHREN UND SYSTEM ZUM BETRIEB EINES TECHNISCHEN GERÄTS 审中-公开
公开(公告)号：EP4455948A1
公开(公告)日：2024-10-30
申请号：EP23169732.7
申请日：2023-04-25
申请人： Siemens Aktiengesellschaft
发明人： REZAPOUR LAKANI, Safoura , HIESSL, Thomas , EDER, Jana , SCHALL, Daniel
IPC分类号： G06N3/098 , G06N3/082 , G06N3/09
CPC分类号： G06N3/098 , G06N3/09 , G06N3/082
摘要： Computer-implementiertes Verfahren zum Betreiben eines technischen Geräts (TD) mit einem Modell auf Basis künstlicher Intelligenz durch einen Klienten (C1-C3) eines Klienten-Server-Systems, wobei jeder Klient (C1-C3) ein Klienten-Modell (CM1-CM3) zum Betrieb eines verbundenen technischen Geräts (TD1) speichert, und folgende Schritte ausgeführt werden:
a) Bereitstellen des globalen Modells (GM) auf Basis föderierten Lernens an einen Klienten (C1),
b) Prüfen durch den Klienten (C1-C3), ob im Speicher (MEM) ein sensitiver Modell-Parameter gespeichert ist, welcher nicht vom globalen Modell (GM) umfasst ist, und falls ja, Aggregieren des bereitgestellten globalen Modells (GM) mit dem sensitiven Modell-Parameter, und Aktualisieren des Klienten-Modells (CM1) mit dem bereitgestellten globalen Modell (GM),
c) Bereitstellen eines Referenz-Datensatzes,
d) Berechnen einer ersten Genauigkeit des Klienten-Modells (CM1) mithilfe des Referenz-Datensatzes,
e) Bestimmen der Gradienten der Modell-Parameter des Klienten-Modells (CM1) und Bestimmen eines ausgewählten Gradienten der Modell-Parameter des Klienten-Modells (CM1),
f) Entfernen des Modell-Parameters, welcher zu dem ausgewählten Gradienten zugehörig ist, aus dem Klienten-Modell (CM1),
g) Berechnen einer zweiten Genauigkeit des Klienten-Modells (CM1) mithilfe des Referenz-Datensatzes,
h) Prüfen, ob sich die zweite Genauigkeit unter der ersten Genauigkeit liegt, falls ja, Festlegen des zumindest einen Modell-Parameters, welcher zu dem zumindest einen ausgewählten Gradienten zugehörig ist, als sensitiver Parameter, und Bereitstellen des Klienten-Modells (CM1) an den Server (S)
i) Aktualisieren des globalen Modells,
j) Betreiben des technischen Geräts (TD1) mit dem Klienten-Modell (CM1) und dem sensitiven Parameter.

3. 发明公开

EP4453764A1 MODULE ET PROCÉDÉ DE SÉCURISATION D'UN ÉQUIPEMENT INFORMATIQUE 失效
公开(公告)号：EP4453764A1
公开(公告)日：2024-10-30
申请号：EP22818849.6
申请日：2022-11-23
申请人： Orange
发明人： SANCHEZ-LEIGHTON, Vincente , GONZALEZ, Laurent
IPC分类号： G06F21/52 , G06F21/64 , G06F21/79 , G06F12/14 , G06F13/16 , G06N3/063 , G06F13/28
CPC分类号： G06F12/1441 , G06F2212/105220130101 , G06F21/79 , G06F13/28 , G06N3/09

4. 发明授权

EP4083839B1 DATA PROTECTION METHOD AND APPARATUS, AND SERVER AND MEDIUM 有权
公开(公告)号：EP4083839B1
公开(公告)日：2024-10-30
申请号：EP21836952.8
申请日：2021-06-25
IPC分类号： G06F21/62 , G06N3/048 , G06N20/00 , G06N3/084 , G06N3/09 , G06N3/091
CPC分类号： G06N3/084 , G06N3/09 , G06N3/091 , G06N3/048 , G06F21/6245

5. 发明公开

EP4451287A1 PREDICTING VASCULAR BEHAVIOR USING A VASCULAR TWIN 审中-公开
公开(公告)号：EP4451287A1
公开(公告)日：2024-10-23
申请号：EP23305610.0
申请日：2023-04-19
申请人： Dassault Systèmes
发明人： BENMAHDI, Meryem , HERMANN, Everton , LIBES, Hugo
IPC分类号： G16H50/50 , G06N3/045
CPC分类号： G16H50/50 , G06N3/045 , G06N3/09
摘要： The disclosure notably relates to a computer-implemented method for predicting vascular behavior of a patient, in particular a hemodynamic behavior. The method comprises providing a vascular model of a circulatory system, one or more measurements of the vascular behavior of the patient, and a surrogate model comprising an artificial neural network. The vascular model represents a general vascular behavior and comprises a plurality of physiological parameters. The surrogate model is configured to predict a simulation of a vascular behavior from the physiological parameters. The method further comprises calibrating the vascular model using the surrogate model and based on the one or more measurements; and predicting the vascular behavior of the patient using the calibrated vascular model.

6. 发明公开

EP4451177A1 GROUP PERSONALIZED FEDERATED LEARNING 审中-公开
公开(公告)号：EP4451177A1
公开(公告)日：2024-10-23
申请号：EP24170582.1
申请日：2024-04-16
申请人： Meta Platforms Technologies, LLC
发明人： Zhe, Liu , Yue, Hui , Fuchun, Peng
IPC分类号： G06N3/09 , G06N3/098
CPC分类号： G06N3/098 , G06N3/09
摘要： A system and method facilitating group personalized federated learning are provided. The system may provide a global machine learning model, generated based on federated learning, to communication devices. The system may also receive model parameters from the communication devices based in part on the communication devices determining local training data generated by the communication devices implementing the global machine learning model. The system may also determine, based on the model parameters from the communication devices, groups of the communication devices and may assign a group specific machine learning model(s), among a plurality of group specific machine learning models, to the groups. The plurality of group specific machine learning models may be associated with the global machine learning model. The system may also provide respective group specific machine learning models, among the plurality of group specific machine learning models, to subsets of communication devices of the groups of the communication devices.

7. 发明公开

EP4451037A1 CONSTRUCTION OF A DIGITAL IMAGE DEPICTING A SAMPLE 审中-公开
公开(公告)号：EP4451037A1
公开(公告)日：2024-10-23
申请号：EP23169073.6
申请日：2023-04-20
申请人： CellaVision AB
发明人： Almers, Martin , Hedlund, Sven , Jönsson, Jesper
IPC分类号： G02B21/36 , G06F18/214 , G06F18/21 , G06N3/00
CPC分类号： G02B21/367 , G06N3/09 , G06N3/0464 , G06V10/145 , G06V10/774 , G06V20/693 , G06V10/764 , G06V10/141 , G06V10/82 , G06V10/776
摘要： The present inventive concept relates to a method and a device for training a machine learning model to construct a digital image depicting a sample. The method (30) comprising: receiving (S300) a training set of digital images of a training sample (1080), wherein the training set of digital images is acquired (S310) using a first microscope objective (104) and by: illuminating (S312) the training sample (1080) with a plurality of illumination patterns, and capturing (S314) a digital image for each illumination pattern of the plurality of illumination patterns; receiving (S320) a ground truth comprising a digital image depicting the training sample (1080), wherein the digital image of the ground truth is acquired (S330) using a second microscope objective (204) and by: illuminating (S332) the training sample with a conventional microscopy illumination pattern, and capturing (S334) the digital image while the training sample (1080) is illuminated with the conventional microscopy illumination pattern; and training (S340) the machine learning model to construct a digital image depicting the training sample (1080) using the received training set of digital images and the received ground truth; and wherein the second microscope objective (204) has a higher numerical aperture than the first microscope objective (104), whereby a resolution of the digital image of the ground truth is higher than a resolution of at least one digital image of the training set of digital images. The present inventive concept further relates to a method and a microscope arrangement for constructing a digital image depicting a sample.

8. 发明公开

EP4448254A1 POWDER DEGRADATION PREDICTIONS 失效
公开(公告)号：EP4448254A1
公开(公告)日：2024-10-23
申请号：EP21968326.5
申请日：2021-12-13
申请人： Hewlett-Packard Development Company, L.P.
发明人： WRIGHT, Jacob, Tyler , KOTHARI, Sunil , CATANA SALAZAR, Juan, Carlos , CHEN, Lei , LEYVA MENDIVIL, Maria, Fabiola , ZENG, Jun
IPC分类号： B29C64/386 , B33Y50/00
CPC分类号： Y02P10/25 , B29C64/153 , B29C64/277 , B33Y10/00 , B29C64/386 , B33Y50/00 , G06N3/0464 , G06N3/044 , G06N3/09 , B22F10/34 , B22F10/80 , B22F10/73 , B22F2999/0020130101 , G06F2113/1020200101 , G06F30/27

9. 发明公开

EP4446944A1 EFFICIENT ACTIVE LEARNING 审中-公开
公开(公告)号：EP4446944A1
公开(公告)日：2024-10-16
申请号：EP23168109.9
申请日：2023-04-14
申请人： aiMotive Kft.
发明人： Matuszka, Tamás , Németh, Gábor
IPC分类号： G06N3/0464 , G06N3/09 , G06N3/0985 , G06N3/091
CPC分类号： G06N3/0464 , G06N3/09 , G06N3/0985 , G06N3/091
摘要： The present invention provides a method for assisted training of a machine learning model for computer-assisted vehicle control, the method comprising, in an iterative manner:
- sampling one or more candidate datapoints from a set of unlabelled datapoints,
- computing an acquisition function of the candidate datapoints,
- if for a first datapoint in the set of unlabelled datapoints a first condition relating to a first value of the acquisition function for the first datapoint is fulfilled, removing the first datapoint from the set of unlabelled datapoints,
- if for a second datapoint in the set of candidate datapoints a second condition relating to a second value of the acquisition function for the second datapoint is fulfilled, obtaining a label for the second datapoint and adding the second datapoint with the label to a set of labelled datapoints, and
- training the machine learning model using the set of labelled datapoints.

10. 发明公开

EP4445680A2 APPLICATION-BASED INCUMBENT INFORMING CAPABILITY FOR SPECTRUM SHARING 审中-实审
公开(公告)号：EP4445680A2
公开(公告)日：2024-10-16
申请号：EP22932479.3
申请日：2022-12-08
申请人： A10 Systems LLC
发明人： MODY, Apurva N. , SIMPSON, David
IPC分类号： H04W72/542 , H04W16/22 , H04W72/12
CPC分类号： H04W72/0453 , H04W16/14 , G06N3/04 , G06N20/00 , G06N3/09

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