公开(公告)号：US11893086B2

公开(公告)日：2024-02-06

申请号：US17197678

申请日：2021-03-10

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Dan Levi ,  Noa Garnett ,  Roy Uziel

IPC: G06F18/00 ,  G06F18/241 ,  G06N3/08 ,  G06V20/56 ,  G06F18/214

CPC classification number: G06F18/241 ,  G06F18/214 ,  G06N3/08 ,  G06V20/56

Abstract: A system for analyzing images includes a processing device includes a receiving module configured to receive an image, and an analysis module configured to apply the received image to a machine learning network and classify one or more features in the received image, the machine learning network configured to propagate image data through a plurality of convolutional layers, each convolutional layer of the plurality of convolutional layers including a plurality of filter channels, the machine learning network including a bottleneck layer configured to recognize an image feature based on a shape of an image component, The system also includes an output module configured to output characterization data that includes a classification of the one or more features.

公开(公告)号：US20250162613A1

公开(公告)日：2025-05-22

申请号：US18511539

申请日：2023-11-16

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Roy Uziel ,  Oded Bialer ,  Claudia Goldman-shenhar

IPC: B60W60/00 ,  B60W30/095 ,  G06V20/58

Abstract: A system includes: a traffic object detection module detecting traffic objects in an environment; an attention map highlighting module generating an attention map, highlighting relevant ones of the traffic objects or regions in which the relevant ones of the traffic objects are located; an image encoder, based on the attention map, encoding an image of the environment and generating an image embedding vector; a PLM module iteratively selecting and appending text to create a text message including selecting the text based on a score, the text message being a specific description of what is perceived in the environment; a text encoder encoding a portion of the text message created thus far to generate a text embedding vector; and a module, based on the image and text embedding vectors, to score the portion to generate the score, where the PLM module is configured to update the portion based on the score.

公开(公告)号：US20250100577A1

公开(公告)日：2025-03-27

申请号：US18474741

申请日：2023-09-26

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Roy Uziel ,  Oded Bialer

IPC: B60W60/00 ,  B60W50/06

Abstract: A method for controlling automated vehicle acceleration and braking includes obtaining an image using at least one vehicle camera of a host vehicle, extracting machine learning model feature inputs based on the obtained image, detecting one or more objects in the obtained image, the one or more objects including at least one pedestrian, assigning attention weights to regions of the obtained image according to locations of the one or more objects in the obtained image, combining the attention weights with corresponding ones of the machine learning model feature inputs according to the regions of the obtained image, executing a machine learning model to generate a crossing intention prediction output associated with the at least one pedestrian, and in response to the crossing intention prediction output exceeding a crossing intention threshold, controlling automatic braking of the host vehicle according to a location of the at least one pedestrian.

公开(公告)号：US20250037424A1

公开(公告)日：2025-01-30

申请号：US18359397

申请日：2023-07-26

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Roy Uziel ,  Oded Bialer ,  Dan Levi

IPC: G06V10/764 ,  G06F40/56 ,  G06V10/774

Abstract: Herein, a technology that facilitates the optimization of vision-language (VL) based classifiers with text embeddings is discussed. The technology includes tuning the VL-based classifier employing a pre-trained image encoder of a visual-language model (VLM) for imaging embedding of pre-classified images and a pre-trained textual encoder of the VLM for textual embedding of a set of differing textual sentences. The technology further includes determining an optimized set of differing textual sentences of a superset of textual sentences. The optimized set of differing textual sentences has a minimal classification loss of the VL-based classifier when classifying the pre-classified images.

公开(公告)号：US20240371132A1

公开(公告)日：2024-11-07

申请号：US18311393

申请日：2023-05-03

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Roy Uziel ,  Oded Bialer ,  Dan Levi

IPC: G06V10/764 ,  G06V10/74 ,  G06V10/82 ,  G06V10/98 ,  G06V20/52 ,  G06V20/58 ,  G06V40/10 ,  G08G1/0967

Abstract: A system for classifying a road crossing intention of a pedestrian includes a processor including a pretrained image encoder generating an image embedding based upon an input image. The system further includes a remote server receiving the image embedding. The remote server device further references a plurality of pretrained image and text embeddings each corresponding to either a positive road crossing intention or a negative road crossing intention. The remote server device further determines a plurality of proximity values evaluating whether the input image is closer to the positive road crossing intention or the negative road crossing intention, evaluating the image embedding against each of the pretrained embeddings. The remote server device further classifies a road crossing intention of the pedestrian based upon the plurality of proximity values. The system further includes generates a road crossing intention output based upon the road crossing intention of the pedestrian.

公开(公告)号：US20220292316A1

公开(公告)日：2022-09-15

申请号：US17197678

申请日：2021-03-10

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Dan Levi ,  Noa Garnett ,  Roy Uziel

IPC: G06K9/62 ,  G06K9/00 ,  G06N3/08

Abstract: A system for analyzing images includes a processing device includes a receiving module configured to receive an image, and an analysis module configured to apply the received image to a machine learning network and classify one or more features in the received image, the machine learning network configured to propagate image data through a plurality of convolutional layers, each convolutional layer of the plurality of convolutional layers including a plurality of filter channels, the machine learning network including a bottleneck layer configured to recognize an image feature based on a shape of an image component, The system also includes an output module configured to output characterization data that includes a classification of the one or more features.