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Patent Agency Ranking
公开(公告)号：US20210390728A1
公开(公告)日：2021-12-16
申请号：US17412574
申请日：2021-08-26
Inventor： Yan PENG , Xiang Long , Shumin Han , Honghui Zheng , Zhuang Jia , Xiaodi Wang , Pengcheng Yuan , Yuan Feng , Bin Zhang , Ying Xin
Abstract: An object area measurement method and an apparatus are provided, relating to the computer vision and deep learning technology. The method includes acquiring an original image with a spatial resolution, the original image including a target object; acquiring an object identification model including at least two sets of classification models; generating one or more original image blocks based on the original image; performing operations on each original image block: scaling each original image block at at least two scaling levels to obtain scaled image blocks with at least two sizes, the scaled image blocks respectively corresponding to the at least two sets of classification models, and inputting the scaled image blocks into the object identification model to obtain an identification result of the target object; and determining an area of the target object based on the respective identification results of the one or more original image blocks and the spatial resolution.
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公开(公告)号：US20210350173A1
公开(公告)日：2021-11-11
申请号：US17379428
申请日：2021-07-19
Inventor： Xiang LONG , Yan PENG , Shufei LIN , Ying XIN , Bin ZHANG , Pengcheng YUAN , Xiaodi WANG , Yuan FENG , Shumin HAN
Abstract: Provided are a method and apparatus for evaluating image relative definition, a device and a medium, relating to technologies such as computer vision, deep learning and intelligent medical. A specific implementation solution is: extracting a multi-scale feature of each image in an image set, where the multi-scale feature is used for representing definition features of objects having different sizes in an image; and scoring relative definition of each image in the image set according to the multi-scale feature by using a relative definition scoring model pre-trained, where the purpose for training the relative definition scoring model is to learn a feature related to image definition in the multi-scale feature.
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公开(公告)号：US20220147822A1
公开(公告)日：2022-05-12
申请号：US17459066
申请日：2021-08-27
Inventor： Ying XIN , Yuan FENG , Guanzhong WANG , Pengcheng YUAN , Bin ZHANG , Xiaodi WANG , Xiang LONG , Yan PENG , Honghui ZHENG , Shumin HAN
IPC: G06N3/08 , G06N3/04 , G06V10/82 , G06V10/766 , G06V10/77
Abstract: Provided are a training method and apparatus for a target detection model, a device and a storage medium. The training method is described below. A feature map of a sample image is processed through a classification network of an initial model and a heat map and a classification prediction result of the feature map are obtained, a classification loss value is determined according to the classification prediction result and classification supervision data of the sample image, and a category probability of pixels in the feature map is determined according to the heat map of the feature map and a probability distribution map of the feature map is obtained; the feature map is processed through a regression network of the initial model and a regression prediction result is obtained, and a regression loss value is determined.
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4.发明申请公开(公告)号：US20220020175A1
公开(公告)日：2022-01-20
申请号：US17489991
申请日：2021-09-30
Inventor： Xiaodi WANG , Shumin HAN , Yuan FENG , Ying XIN , Bin ZHANG , Xiang LONG , Honghui ZHENG , Yan PENG , Zhuang JIA
Abstract: An object detection model training method, object detection method and related apparatus, relate to the field of artificial intelligence technologies such as computer vision, deep learning. An implementation includes: obtaining training sample data including a first remote sensing image and position annotation information of an anchor box of a subject to be detected in the first remote sensing image, where the position annotation information includes angle information of the anchor box relative to a preset direction; obtaining an object feature map of the first remote sensing image based on an object detection model, performing object detection on the subject to be detected based on the object feature map to obtain an object bounding box, and determining loss information between the anchor box and the object bounding box based on the angle information; updating a parameter of the object detection model based on the loss information.
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公开(公告)号：US20210312240A1
公开(公告)日：2021-10-07
申请号：US17348285
申请日：2021-06-15
Inventor： Xiaodi WANG , Shumin HAN , Yuan FENG , Ying XIN , Bin ZHANG , Shufei LIN , Pengcheng YUAN , Xiang LONG , Yan PENG , Honghui ZHENG
Abstract: A header model for instance segmentation includes a target box branch having a first branch and a second branch, where the first branch is configured to process an inputted first feature map to obtain class information and confidence of a target box, and the second branch is configured to process the first feature map to obtain location information of the target box. The header model also includes a mask branch configured to process an inputted second feature map to obtain mask information, wherein the second feature map is a feature map outputted by an ROI extraction module, and the first feature map is a feature map resulting from a pooling performed on the second feature map.
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