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公开(公告)号：US20230008696A1
公开(公告)日：2023-01-12
申请号：US17939364
申请日：2022-09-07
Inventor： Yunhao WANG , Bin ZHANG , Ying XIN , Yuan FENG , Shumin HAN
IPC: G06T5/00 , G06V10/22 , G06V10/774 , G06T5/50
Abstract: The present disclosure provides a method for incrementing a sample image, an electronic device, and a computer readable storage medium. A specific implementation comprises: acquiring a first convolutional feature of an original sample image; determining, according to a region generation network and the first convolutional feature, a candidate region and a first probability that the candidate region contains a target object; determining a target candidate region from the candidate region based on the first probability, and mapping the target candidate region back to the original sample image to obtain an intermediate image; and performing image enhancement processing on a portion of the intermediate image corresponding to the target candidate region and/or performing image blur processing on a portion of the intermediate image corresponding to a non-target candidate region to obtain an incremental sample image.
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公开(公告)号：US20210224526A1
公开(公告)日：2021-07-22
申请号：US17164613
申请日：2021-02-01
Inventor： Mingyuan MAO , Yuan FENG , Ying XIN , Pengcheng YUAN , Bin ZHANG , Shufei LIN , Xiaodi WANG , Shumin HAN , Yingbo XU , Jingwei LIU , Shilei WEN , Hongwu Zhang , Errui DING
Abstract: The present application discloses a method and an apparatus for detecting wearing of a safety helmet, a device and a storage medium. The method for detecting wearing of a safety helmet includes: acquiring a first image collected by a camera device, where the first image includes at least one human body image; determining the at least one human body image and at least one head image in the first image; determining a human body image corresponding to each head image in the at least one human body image according to an area where the at least one human body image is located and an area where the at least one head image is located; and processing the human body image corresponding to the at least one head image according to a type of the at least one head image.
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公开(公告)号：US20230066021A1
公开(公告)日：2023-03-02
申请号：US18049742
申请日：2022-10-26
Inventor： Yunhao WANG , Bin ZHANG , Chao LI , Yan PENG , Song CHEN , Song XUE , Yuan FENG , Shumin HAN
Abstract: A method is provided that includes: segmenting an image to be detected into a plurality of image blocks; generating a feature representation of the image to be detected based on the plurality of image blocks; mapping the feature representation by using a preset parameter set to obtain a plurality of feature maps of the image to be detected; and determining a position and a class of a target object in the image to be detected based on the plurality of feature maps.
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公开(公告)号：US20220301131A1
公开(公告)日：2022-09-22
申请号：US17743057
申请日：2022-05-12
Inventor： Jingwei LIU , Yi GU , Xuhui LIU , Xiaodi WANG , Shumin HAN , Yuan FENG , Ying XIN , Chao LI , Bin ZHANG , Honghui ZHENG , Xiang LONG , Yan PENG , Errui DING , Yunhao WANG
Abstract: A method for generating a sample image includes: obtaining an initial image size of an initial image; obtaining a plurality of reference images by processing the initial image based on different reference processing modes; obtaining an image to be processed by fusing the plurality of reference images; and determining a target sample image from images to be processed based on the initial image size.
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Patent Agency Ranking
公开(公告)号：US20220148190A1
公开(公告)日：2022-05-12
申请号：US17579425
申请日：2022-01-19
Inventor： Xiang LONG , Yan PENG , Honghui ZHENG , Zhuang JIA , Bin ZHANG , Xiaodi WANG , Pengcheng YUAN , Ying XIN , Yuan FENG , Shumin HAN
Abstract: The disclosure provides a method for detecting a change of a building, an apparatus for detecting a change of a building, an electronic device, a storage medium and a computer program product. The method includes: obtaining a remote-sensing image sequence of a to-be-detected region; obtaining a building probability map corresponding to each remote-sensing image in the remote-sensing image sequence; determining a sub-region located by each building in the to-be-detected region based on the building probability map corresponding to each remote-sensing image; for each building, determining an existence probability of the building in each remote-sensing image based on the sub-region located by the building and the building probability map corresponding to each remote-sensing image; and determining a change condition of the building based on the existence probability of the building in each remote-sensing image.
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6.发明公开公开(公告)号：US20240193923A1
公开(公告)日：2024-06-13
申请号：US17908070
申请日：2022-01-29
Inventor： Xiaodi WANG , Shumin HAN , Yuan FENG , Ying XIN , Yi GU , Bin ZHANG , Chao LI , Xiang LONG , Honghui ZHENG , Yan PENG , Zhuang JIA , Yunhao WANG
IPC: G06V10/778
CPC classification number: G06V10/778 , G06V2201/07
Abstract: A method of training a target object detection model includes: extracting a plurality of feature maps of a sample image according to a training parameter, fusing the plurality of feature maps to obtain at least one fused feature map, and obtaining an information of a target object based on the at least one fused feature map, by using the target object detection model; determining a loss of the target object detection model based on the information of the target object and a tag information of the sample image, and adjusting the training parameter according to the loss of the target object detection model. A method of detecting a target object and an apparatus are also provided.
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公开(公告)号：US20230196716A1
公开(公告)日：2023-06-22
申请号：US18173689
申请日：2023-02-23
Inventor： Yuan FENG , Zhun SUN , Honghui ZHENG , Ying XIN , Bin ZHANG , Chao LI , Yunhao WANG , Shumin HAN
IPC: G06V10/44 , G06V10/774 , G06V10/764
CPC classification number: G06V10/443 , G06V10/774 , G06V10/764
Abstract: A method for training a multi-target image-text matching model and an image-text retrieval method are provided. The method for training the multi-target image-text matching model includes: obtaining a plurality of training samples that include sample pairs each including a sample image and a sample text, the sample image including a plurality of targets; obtaining, for each of the plurality of training samples, a heat map corresponding to the sample text in the training sample, the heat map representing a region of the target in the sample image that corresponds to the sample text; and training an image-text matching model based on a plurality of the sample texts and corresponding heat maps to obtain the multi-target image-text matching model.
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公开(公告)号：US20230068025A1
公开(公告)日：2023-03-02
申请号：US17981965
申请日：2022-11-07
Inventor： Yan PENG , Xiang LONG , Honghui ZHENG , Zhuang JIA , Bin ZHANG , Xiaodi WANG , Ying XIN , Yi GU , Yunhao WANG , Chao LI , Yuan FENG , Shumin HAN
Abstract: A method for generating a road annotation, a device, and a storage medium are provided. The method may include: generating a road quantity and a road width in a tag picture; generating, for each road in the tag picture, a start point and an end point of the road; generating at least one point between the start point and the end point; drawing, for two adjacent points, a line segment from a previous point to a next point, where a width of the line segment is equal to the road width; and generating slanted box annotation information based on a coordinate of the previous point and a coordinate of the next point, where the slanted box annotation information includes an intersection point of diagonal lines, a width, a height and a slant angle of a slanted box.
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公开(公告)号：US20220036068A1
公开(公告)日：2022-02-03
申请号：US17504188
申请日：2021-10-18
Inventor： Yan PENG , Xiang LONG , Honghui ZHENG , Zhuang JIA , Bin ZHANG , Xiaodi WANG , Ying XIN , Yi GU , Yunhao WANG , Chao LI , Yuan FENG , Shumin HAN
Abstract: The disclosure provides a method for recognizing an image, an apparatus for recognizing an image, an electronic device and a storage medium. An image to be processed is obtained. The number of first channels of the image is greater than the number of second channels of a red-green-blue (RGB) image. For each pixel of the image, a semantic type of the pixel is determined based on a value of the pixel on each channel. A recognition result of the image is generated based on the image and the semantic type of each pixel.
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