公开(公告)号：US20220383146A1

公开(公告)日：2022-12-01

申请号：US17804652

申请日：2022-05-31

申请人： Aptiv Technologies Limited

发明人： Markus Schoeler ,  Jan Siegemund ,  Christian Nunn ,  Yu Su ,  Mirko Meuter ,  Adrian Becker ,  Peet Cremer

IPC分类号： G06N5/02 ,  G01S7/41

摘要： A method is provided for training a machine-learning algorithm which relies on primary data captured by at least one primary sensor. Labels are identified based on auxiliary data provided by at least one auxiliary sensor. A care attribute or a no-care attribute is assigned to each label by determining a perception capability of the primary sensor for the label based on the primary data and based on the auxiliary data. Model predictions for the labels are generated via the machine-learning algorithm. A loss function is defined for the model predictions. Negative contributions to the loss function are permitted for all labels. Positive contributions to the loss function are permitted for labels having a care attribute, while positive contributions to the loss function for labels having a no-care attribute are permitted only if a confidence of the model prediction for the respective label is greater than a threshold.

公开(公告)号：US20220292806A1

公开(公告)日：2022-09-15

申请号：US17653208

申请日：2022-03-02

申请人： Aptiv Technologies Limited

发明人： Yu Su ,  Markus Schoeler

IPC分类号： G06V10/40 ,  G06V20/56 ,  G01S17/931 ,  G01S17/86 ,  G06V10/82 ,  G06N3/04

摘要： A computer implemented method for object detection the following steps carried out by computer hardware components: determining an output of a first pooling layer based on input data; determining an output of a dilated convolution layer, provided directly after the first pooling layer, based on the output of the first pooling layer; determining an output of a second pooling layer, provided directly after the dilated convolution layer, based on the output of the dilated convolution layer; and carrying out the object detection based on at least the output of the dilated convolution layer or the output of the second pooling layer.

公开(公告)号：US20220221303A1

公开(公告)日：2022-07-14

申请号：US17647306

申请日：2022-01-06

申请人： Aptiv Technologies Limited

发明人： Mirko Meuter ,  Christian Nunn ,  Weimeng Zhu ,  Florian Kaestner ,  Adrian Becker ,  Markus Schoeler

IPC分类号： G01C21/00 ,  G01S13/89 ,  G01S19/41 ,  G06T7/30 ,  G06T7/73 ,  G06N3/08

摘要： A computer implemented method for determining a location of an object comprises the following steps carried out by computer hardware components: determining a pre-stored map of a vicinity of the object; acquiring sensor data related to the vicinity of the object; determining an actual map based on the acquired sensor data; carrying out image registration based on the pre-stored map and the actual map; carrying out image registration based on the image retrieval; and determining a location of the object based on the image registration.

公开(公告)号：US20220026568A1

公开(公告)日：2022-01-27

申请号：US17384493

申请日：2021-07-23

申请人： Aptiv Technologies Limited

发明人： Mirko Meuter ,  Jittu Kurian ,  Yu Su ,  Jan Siegemund ,  Zhiheng Niu ,  Stephanie Lessmann ,  Saeid Khalili Dehkordi ,  Florian Kästner ,  Igor Kossaczky ,  Sven Labusch ,  Arne Grumpe ,  Markus Schoeler ,  Moritz Luszek ,  Weimeng Zhu ,  Adrian Becker ,  Alessandro Cennamo ,  Kevin Kollek ,  Marco Braun ,  Dominic Spata ,  Simon Roesler

IPC分类号： G01S13/931 ,  G06K9/00 ,  G06K9/62 ,  G01S13/86 ,  G01S7/41 ,  B60W60/00 ,  G06N3/04

摘要： A computer implemented method for detection of objects in a vicinity of a vehicle comprises the following steps carried out by computer hardware components: acquiring radar data from a radar sensor; determining a plurality of features based on the radar data; providing the plurality of features to a single detection head; and determining a plurality of properties of an object based on an output of the single detection head.