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1.发明授权公开(公告)号：US11604949B2
公开(公告)日：2023-03-14
申请号：US17034486
申请日：2020-09-28
Inventor： Ke Zhou Yan
Abstract: An image processing method is provided. The method includes obtaining at least two images, the at least two images being based on the same target object captured from different imaging angles, respectively; extracting, by using feature extraction networks included in an image processing model, target features of the at least two images, the feature extraction networks being configured to extract features of images corresponding to the different imaging angles, respectively; and determining, based on the target features, a classification result corresponding to the target object.
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2.发明申请公开(公告)号：US20210019551A1
公开(公告)日：2021-01-21
申请号：US17034486
申请日：2020-09-28
Inventor： Ke Zhou Yan
Abstract: An image processing method is provided. The method includes obtaining at least two images, the at least two images being based on the same target object captured from different imaging angles, respectively; extracting, by using feature extraction networks included in an image processing model, target features of the at least two images, the feature extraction networks being configured to extract features of images corresponding to the different imaging angles, respectively; and determining, based on the target features, a classification result corresponding to the target object.
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公开(公告)号：US20200320701A1
公开(公告)日：2020-10-08
申请号：US16905079
申请日：2020-06-18
Inventor： Fen Xiao , Jia Chang , Xuan Zhou , Ke Zhou Yan , Cheng Jiang , Kuan Tian , Jian Ping Zhu
Abstract: An image processing method performed by a terminal is provided. A molybdenum target image is obtained, and a plurality of candidate regions are extracted from the molybdenum target image. In the molybdenum target image, a target region is marked in the plurality of candidate regions by using a neural network model obtained by deep learning training, a probability that a lump comprised in the target region is a target lump being greater than a first threshold, a probability that the target lump is a malignant tumor being greater than a second threshold, and the neural network model being used for indicating a mapping relationship between a candidate region and a probability that a lump comprised in the candidate region is the target lump.
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公开(公告)号：US11501431B2
公开(公告)日：2022-11-15
申请号：US16905079
申请日：2020-06-18
Inventor： Fen Xiao , Jia Chang , Xuan Zhou , Ke Zhou Yan , Cheng Jiang , Kuan Tian , Jian Ping Zhu
Abstract: An image processing method performed by a terminal is provided. A molybdenum target image is obtained, and a plurality of candidate regions are extracted from the molybdenum target image. In the molybdenum target image, a target region is marked in the plurality of candidate regions by using a neural network model obtained by deep learning training, a probability that a lump comprised in the target region is a target lump being greater than a first threshold, a probability that the target lump is a malignant tumor being greater than a second threshold, and the neural network model being used for indicating a mapping relationship between a candidate region and a probability that a lump comprised in the candidate region is the target lump.
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