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公开(公告)号：US20220410939A1
公开(公告)日：2022-12-29
申请号：US17901428
申请日：2022-09-01
Inventor： Lei ZHANG , Kai YANG , Qijuan YIN , Wuzhao ZHANG , Xiaoyan WANG
Abstract: A collision detection method, an electronic device, and a storage medium are provided, which relate to a field of artificial intelligence technology, and in particular to fields of intelligent transportation and autonomous driving technologies. The method includes: determining a predicted travel range of a target object based on a planned travel trajectory of the target object and a historical travel trajectory of the target object; determining, in response to a target obstacle being detected, a predicted travel range of the target obstacle based on a current travel state of the target obstacle; and determining whether the target object has a risk of colliding with the target obstacle, based on the predicted travel range of the target object and the predicted travel range of the target obstacle.
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Patent Agency Ranking
公开(公告)号：US20230215203A1
公开(公告)日：2023-07-06
申请号：US18168759
申请日：2023-02-14
Inventor： Pengyuan LV , Chengquan ZHANG , Shanshan LIU , Meina QIAO , Yangliu XU , Liang WU , Xiaoyan WANG , Kun YAO , Junyu Han , Errui DING , Jingdong WANG , Tian WU , Haifeng WANG
IPC: G06V30/19
CPC classification number: G06V30/19147 , G06V30/19167
Abstract: The present disclosure provides a character recognition model training method and apparatus, a character recognition method and apparatus, a device and a medium, relating to the technical field of artificial intelligence, and specifically to the technical fields of deep learning, image processing and computer vision, which can be applied to scenarios such as character detection and recognition technology. The specific implementing solution is: partitioning an untagged training sample into at least two sub-sample images; dividing the at least two sub-sample images into a first training set and a second training set; where the first training set includes a first sub-sample image with a visible attribute, and the second training set includes a second sub-sample image with an invisible attribute; performing self-supervised training on a to-be-trained encoder by taking the second training set as a tag of the first training set, to obtain a target encoder.
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公开(公告)号：US20240304015A1
公开(公告)日：2024-09-12
申请号：US18041265
申请日：2022-04-21
Inventor： Sen FAN , Xiaoyan WANG , Pengyuan LV , Chengquan ZHANG , Kun YAO
IPC: G06V30/19 , G06V30/148 , G06V30/18
CPC classification number: G06V30/19167 , G06V30/153 , G06V30/18 , G06V30/19147 , G06V30/1916
Abstract: The present disclosure provides a method of training a deep learning model for text detection and a text detection method, which relates to the technical field of artificial intelligence, and in particular, to the technical field of computer vision and deep learning and can be used in scenarios of OCR optical character recognition. A method of training a deep learning model for text detection is provided, in which a single character segmentation sub-network outputs a single character segmentation prediction result, a text line segmentation sub-network outputs a text line segmentation prediction result, the trained deep learning model can be used for detecting a text area; and, can at the same time achieve single character segmentation and text line segmentation, and thus is capable to perform text detection by combining two ways of text segmentation, which further improves the accuracy of text area detection.
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公开(公告)号：US20230050079A1
公开(公告)日：2023-02-16
申请号：US17974630
申请日：2022-10-27
Inventor： Pengyuan LV , Xiaoyan WANG , Liang WU , Shanshan LIU , Yuechen YU , Meina QIAO , Jie LU , Chengquan ZHANG , Kun YAO
IPC: G06V30/18 , G06V30/148
Abstract: Provided are a text recognition method, an electronic device, and a non-transitory computer-readable storage medium, which are applicable in an OCR scenario. In the particular solution, a text image to be recognized is acquired. Feature extraction is performed on the text image, to obtain an image feature corresponding to the text image, where a height-wise feature and a width-wise feature of the image feature each have a dimension greater than 1. According to the image feature, sampling features corresponding to multiple sampling points in the text image are determined. According to the sampling features corresponding to the multiple sampling points, a character recognition result corresponding to the text image is determined.
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公开(公告)号：US20230010031A1
公开(公告)日：2023-01-12
申请号：US17946464
申请日：2022-09-16
Inventor： Pengyuan LYU , Sen FAN , Xiaoyan WANG , Yuechen YU , Chengquan ZHANG , Kun YAO , Junyu HAN
Abstract: A method for recognizing a text, an electronic device and a storage medium. An implementation of the method comprises: obtaining a multi-dimensional first feature map of a to-be-recognized image; performing, based on feature values in the first feature map, feature enhancement processing on each feature value in the first feature map; and performing a text recognition on the to-be-recognized image based on the first feature map after the enhancement processing.
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公开(公告)号：US20210139052A1
公开(公告)日：2021-05-13
申请号：US17030919
申请日：2020-09-24
Inventor： Lei ZHANG , Kai YANG , Hongda ZHANG , Qijuan YIN , Xiaoyan WANG , Wuzhao ZHANG
Abstract: The present disclosure provides a task scheduling method, an apparatus, a device and a computer readable storage medium provided by the, and an implementation solution thereof includes: identifying obstacle information of an obstacle around a vehicle; determining a safety level of the obstacle according to driving information and the obstacle information of the vehicle; determining a driving task according to the obstacle information, determining a safety level of the driving task according to the safety level of the obstacle corresponding to the obstacle information; and performing a task scheduling according to the safety level of the driving task. The method, the apparatus, the device and the computer readable storage medium provided by the present disclosure can perform the task with the highest safety level preferentially and avoid a situation in which an urgent situation is unable to be dealt with in time.
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