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公开(公告)号：US11468687B2
公开(公告)日：2022-10-11
申请号：US16762757
申请日：2018-10-16
申请人： Robert Bosch GmbH
发明人： Masato Takami , Uwe Brosch
摘要： A method for training a machine learning system, in which image data are fed into a machine learning system with processing of at least a part of the image data by the machine learning system. The method includes synthetic generation of at least a part of at least one depth map that includes a plurality of depth information values. The at least one depth map is fed into the machine learning system with processing of at least a part of the depth information values of the at least one depth map. The machine learning system is then trained based on the processed image data and based on the processed depth information values of the at least one depth map, with adaptation of a parameter value of at least one parameter of the machine learning system, the adapted parameter value influencing an interpretation of input data by the machine learning system.
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公开(公告)号：US20210321038A1
公开(公告)日：2021-10-14
申请号：US17260047
申请日：2019-06-19
申请人： Robert Bosch GmbH
发明人： Dirk Raproeger , Lidia Rosario Torres Lopez , Paul Robert Herzog , Paul-Sebastian Lauer , Uwe Brosch
摘要： A method, including recording a first and a second camera image; the first camera image and the second camera image having an overlap region. The method includes: assigning pixels of the first camera image and pixels of the second camera image to predefined points of a three-dimensional lattice structure, the predefined points being situated in a region of the three-dimensional lattice structure, which represents the overlap region; ascertaining a color information item difference for each predefined point as a function of the assigned color information items; ascertaining a quality value as a function of the ascertained color information item difference at the specific, predefined point; determining a global color transformation matrix as a function of the color information item differences, weighted as a function of the corresponding quality value; and adapting the second camera image as a function of the determined color transformation matrix.
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公开(公告)号：US20210182652A1
公开(公告)日：2021-06-17
申请号：US17110946
申请日：2020-12-03
申请人： Robert Bosch GmbH
发明人： Masato Takami , Uwe Brosch , Dimitrios Bariamis , Emil Schreiber
摘要： An evaluation system for processing measured data which include physical measured data detected with the aid of one or multiple sensors, and/or realistic synthetic measured data of the sensor(s), into one or multiple evaluation results. The system includes at least two input stages independent from each other, which are designed to receive measured data and process these measured data into precursors. At least one processing stage, receives the precursors from all input stages as inputs and is designed to process one or multiple input precursor(s) into a shared intermediate product. At least one output stage, which is designed to process the intermediate product into one or multiple evaluation result(s) of the evaluation system. A method for training the evaluation system. A method for operating the evaluation system is also provided.
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公开(公告)号：US11908142B2
公开(公告)日：2024-02-20
申请号：US17282372
申请日：2019-09-26
申请人： Robert Bosch GmbH
CPC分类号： G06T7/11 , G06N3/045 , G06T2207/20084
摘要： A method for the computing and memory resource-conserving semantic segmentation of image data of an imaging sensor with the aid of an artificial neural network, in particular, a convolutional neural network, the artificial neural network including an encoder path and a decoder path. The method includes: dividing an input tensor into at least one first slice tensor and at least one second slice tensor as a function of a division function, the input tensor being dependent on the image data; outputting the at least one first slice tensor to the decoder path of the neural network; connecting the at least one first slice tensor to the at least one second slice tensor as a function of a connecting function to obtain an output tensor; and outputting the output tensor to the encoder path of the artificial neural network.
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公开(公告)号：US20220019821A1
公开(公告)日：2022-01-20
申请号：US17370331
申请日：2021-07-08
申请人： Robert Bosch GmbH
发明人： Fabian Brickwedde , Uwe Brosch , Masato Takami , Gregor Blott
IPC分类号： G06K9/00 , G06T7/11 , G06K9/62 , H04N19/167
摘要： A method for generating a monitoring image. The method includes: providing an image sequence of the surroundings to be monitored with the aid of an imaging system; determining at least one monitoring area and at least one periphery area of at least one image of the image sequence with the aid of a learning-based semantic segmentation method; compressing the monitoring area of the at least one image of the image sequence with a first compression quality; and compressing the periphery area of the at least one image of the image sequence with a second compression quality to generate the compressed monitoring image, the second compression quality being lower than the first compression quality.
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公开(公告)号：US20240177501A1
公开(公告)日：2024-05-30
申请号：US18519705
申请日：2023-11-27
申请人： Robert Bosch GmbH
发明人： Masato Takami , Fabian Brickwedde , Uwe Brosch
摘要： A method for detecting an end of a journey of a vehicle. The method includes: determining a movement of the vehicle; determining a closing of at least one door of the vehicle; determining an entry and/or an exit of one or more persons into or from the vehicle; detecting the end of the journey of the vehicle when it is determined that the movement of the vehicle is zero, and when a closing of at least the one door of the vehicle is determined, and when an entry and/or an exit of the one or more persons into or from the vehicle is detected.
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公开(公告)号：US11580695B2
公开(公告)日：2023-02-14
申请号：US17049327
申请日：2019-05-09
申请人： Robert Bosch GmbH
发明人： Dirk Raproeger , Lidia Rosario Torres Lopez , Paul Robert Herzog , Paul-Sebastian Lauer , Uwe Brosch
摘要： A method for a sensor-based and memory-based representation of a surroundings of a vehicle. The vehicle includes an imaging sensor for detecting the surroundings. The method includes: detecting a sequence of images; determining distance data on the basis of the detected images and/or of a distance sensor of the vehicle, the distance data comprising distances between the vehicle and objects in the surroundings of the vehicle; generating a three-dimensional structure of a surroundings model on the basis of the distance data; recognizing at least one object in the surroundings of the vehicle on the basis of the detected images, in particular by a neural network; loading a synthetic object model on the basis of the recognized object; adapting the generated three-dimensional structure of the surroundings model on the basis of the synthetic object model and on the basis of the distance data; and displaying the adapted surroundings model.
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公开(公告)号：US20210329219A1
公开(公告)日：2021-10-21
申请号：US17271046
申请日：2019-10-29
申请人： Robert Bosch GmbH
发明人： Dirk Raproeger , Lidia Rosario Torres Lopez , Paul Robert Herzog , Paul-Sebastian Lauer , Uwe Brosch
IPC分类号： H04N13/275 , B60R1/00 , G06N3/08 , G06K9/62 , G06T7/70 , H04N13/239
摘要： A method for enriching a target image, which a target camera system had recorded of a scene, with additional information, with which at least one source image that a source camera system had recorded of the same scene from a different perspective, has already been enriched. The method includes: assigning 3D locations in the three-dimensional space, which correspond to the positions of the source pixels in the source image, to source pixels of the source image; assigning additional information which is assigned to source pixels, to the respective, associated 3D locations; assigning those target pixels of the target image, whose positions in the target image correspond to the 3D locations, to the 3D locations; assigning additional information, which is assigned to 3D locations, to associated target pixels. A method for training a Kl module is also described.
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公开(公告)号：US11100358B2
公开(公告)日：2021-08-24
申请号：US16591151
申请日：2019-10-02
申请人： Robert Bosch GmbH
摘要： A method for the calculation resource-saving semantic segmentation of image data of an imaging sensor with an artificial neural network, in particular, of a convolutional neural network, the artificial neural network including an encoder path, a decoder path (and a skip component), including: initial connection (merge) of an input tensor to a skip tensor with an initial connection (merge) function/connection instruction to obtain a merged tensor, the input tensor and the skip tensor being dependent on the image data; application of a function of a neural network, in particular, of a convolution to the merged tensor to obtain a proof reader tensor; second connection (merge) of the proof reader tensor to the input tensor with a second connection (merge) function/connection instruction to obtain an output tensor; outputting the output tensor to the decoder path of the artificial neural network.
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公开(公告)号：US20210182577A1
公开(公告)日：2021-06-17
申请号：US16762757
申请日：2018-10-16
申请人： Robert Bosch GmbH
发明人： Masato Takami , Uwe Brosch
摘要： A method for training a machine learning system, in which image data are fed into a machine learning system with processing of at least a part of the image data by the machine learning system. The method includes synthetic generation of at least a part of at least one depth map that includes a plurality of depth information values. The at least one depth map is fed into the machine learning system with processing of at least a part of the depth information values of the at least one depth map. The machine learning system is then trained based on the processed image data and based on the processed depth information values of the at least one depth map, with adaptation of a parameter value of at least one parameter of the machine learning system, the adapted parameter value influencing an interpretation of input data by the machine learning system.
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