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公开(公告)号：US11195038B2
公开(公告)日：2021-12-07
申请号：US16374138
申请日：2019-04-03
发明人： Christian Nunn , Weimeng Zhu , Yu Su
IPC分类号： G06K9/00
摘要： A device for extracting dynamic information comprises a convolutional neural network, wherein the device is configured to receive a sequence of data blocks acquired over time, each of said data blocks comprising a multi-dimensional representation of a scene. The convolutional neural network is configured to receive the sequence as input and to output dynamic information on the scene in response, wherein the convolutional neural network comprises a plurality of modules, and wherein each of said modules is configured to carry out a specific processing task for extracting the dynamic information.
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公开(公告)号：US20220261653A1
公开(公告)日：2022-08-18
申请号：US17661912
申请日：2022-05-03
发明人： Weimeng Zhu , Jan Siegemund
摘要： A method of processing image data in a connectionist network includes: determining, a plurality of offsets, each offset representing an individual location shift of an underlying one of the plurality of output picture elements, determining, from the plurality of offsets, a grid for sampling from the plurality of input picture elements, wherein the grid comprises a plurality of sampling locations, each sampling location being defined by means of a respective pair of one of the plurality of offsets and the underlying one of the plurality of output picture elements, sampling from the plurality of input picture elements in accordance with the grid, and transmitting, as output data for at least a subsequent one of the plurality of units of the connectionist network, a plurality of sampled picture elements resulting from the sampling, wherein the plurality of sampled picture elements form the plurality of output picture elements.
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公开(公告)号：US11386329B2
公开(公告)日：2022-07-12
申请号：US16202688
申请日：2018-11-28
发明人： Weimeng Zhu , Jan Siegemund
摘要： A method of processing image data in a connectionist network includes: determining, a plurality of offsets, each offset representing an individual location shift of an underlying one of the plurality of output picture elements, determining, from the plurality of offsets, a grid for sampling from the plurality of input picture elements, wherein the grid comprises a plurality of sampling locations, each sampling location being defined by means of a respective pair of one of the plurality of offsets and the underlying one of the plurality of output picture elements, sampling from the plurality of input picture elements in accordance with the grid, and transmitting, as output data for at least a subsequent one of the plurality of units of the connectionist network, a plurality of sampled picture elements resulting from the sampling, wherein the plurality of sampled picture elements form the plurality of output picture elements.
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公开(公告)号：US11604272B2
公开(公告)日：2023-03-14
申请号：US16904835
申请日：2020-06-18
发明人： Yu Su , Weimeng Zhu , Florian Kästner , Adrian Becker
IPC分类号： G01S13/931 , G01S13/89
摘要： A computer implemented method for object detection includes: determining a grid, the grid comprising a plurality of grid cells; determining, for a plurality of time steps, for each grid cell, a plurality of respective radar detection data, each radar detection data indicating a plurality of radar properties; determining, for each time step, a respective radar map indicating a pre-determined radar map property in each grid cell; converting the respective radar detection data of the plurality of grid cells for the plurality of time steps to a point representation of pre-determined first dimensions; converting the radar maps for the plurality of time steps to a map representation of pre-determined second dimensions, wherein the pre-determined first dimensions and the pre-determined second dimensions are at least partially identical; concatenating the point representation and the map representation to obtain concatenated data; and carrying out object detection based on the concatenated data.
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公开(公告)号：US11521059B2
公开(公告)日：2022-12-06
申请号：US16373939
申请日：2019-04-03
发明人： Weimeng Zhu , Yu Su , Christian Nunn
摘要： A device for processing data sequences by means of a convolutional neural network is configured to carry out the following steps: receiving an input sequence comprising a plurality of data items captured over time using a sensor, each of said data items comprising a multi-dimensional representation of a scene, generating an output sequence representing the input sequence processed item-wise by the convolutional neural network, wherein generating the output sequence comprises: generating a grid-generation sequence based on a combination of the input sequence and an intermediate grid-generation sequence representing a past portion of the output sequence or the grid-generation sequence, generating a sampling grid on the basis of the grid-generation sequence, generating an intermediate output sequence by sampling from the past portion of the output sequence according to the sampling grid, and generating the output sequence based on a weighted combination of the intermediate output sequence and the input sequence.
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6.发明申请公开(公告)号：US20190325306A1
公开(公告)日：2019-10-24
申请号：US16373939
申请日：2019-04-03
发明人： Weimeng Zhu , Yu Su , Christian Nunn
IPC分类号： G06N3/08
摘要： A device for processing data sequences by means of a convolutional neural network is configured to carry out the following steps: receiving an input sequence comprising a plurality of data items captured over time using a sensor, each of said data items comprising a multi-dimensional representation of a scene, generating an output sequence representing the input sequence processed item-wise by the convolutional neural network, wherein generating the output sequence comprises: generating a grid-generation sequence based on a combination of the input sequence and an intermediate grid-generation sequence representing a past portion of the output sequence or the grid-generation sequence, generating a sampling grid on the basis of the grid-generation sequence, generating an intermediate output sequence by sampling from the past portion of the output sequence according to the sampling grid, and generating the output sequence based on a weighted combination of the intermediate output sequence and the input sequence.
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公开(公告)号：US20190171939A1
公开(公告)日：2019-06-06
申请号：US16202688
申请日：2018-11-28
发明人： Weimeng Zhu , Jan Siegemund
摘要： A method of processing image data in a connectionist network includes: determining, a plurality of offsets, each offset representing an individual location shift of an underlying one of the plurality of output picture elements, determining, from the plurality of offsets, a grid for sampling from the plurality of input picture elements, wherein the grid comprises a plurality of sampling locations, each sampling location being defined by means of a respective pair of one of the plurality of offsets and the underlying one of the plurality of output picture elements, sampling from the plurality of input picture elements in accordance with the grid, and transmitting, as output data for at least a subsequent one of the plurality of units of the connectionist network, a plurality of sampled picture elements resulting from the sampling, wherein the plurality of sampled picture elements form the plurality of output picture elements.
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公开(公告)号：US11552778B2
公开(公告)日：2023-01-10
申请号：US16801296
申请日：2020-02-26
发明人： Yu Su , Weimeng Zhu , Mirko Meuter
摘要： A method of multi-sensor data fusion includes determining a plurality of first data sets using a plurality of sensors, each of the first data sets being associated with a respective one of a plurality of sensor coordinate systems, and each of the sensor coordinate systems being defined in dependence of a respective one of a plurality of mounting positions for the sensors; transforming the first data sets into a plurality of second data sets using a transformation rule, each of the second data sets being associated with a unified coordinate system, the unified coordinate system being defined in dependence of at least one predetermined reference point; and determining at least one fused data set by fusing the second data sets.
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公开(公告)号：US20220221303A1
公开(公告)日：2022-07-14
申请号：US17647306
申请日：2022-01-06
发明人： Mirko Meuter , Christian Nunn , Weimeng Zhu , Florian Kaestner , Adrian Becker , Markus Schoeler
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.
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公开(公告)号：US20220188582A1
公开(公告)日：2022-06-16
申请号：US17643586
申请日：2021-12-09
发明人： Weimeng Zhu , Florian Kaestner , Zhiheng Niu , Arne Grumpe
摘要： A method is provided for classifying a tracked object in an environment of a vehicle. The vehicle includes a plurality of radar sensors and a processing device configured to establish a neural network. According to the method, local radar detections are captured from an object in the environment of the vehicle via the radar sensors. Based on the local radar detections, point features and tracker features are determined. The point features are encoded via point encoding layers of the neural network, whereas the tracker features are encoded via track encoding layers of the neural network. A temporal fusion of the encoded point features and the encoded tracker features is performed via temporal fusion layers of the neural network. The tracked object is classified based on the fused encoded point and tracker features via classifying layers of the neural network.
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