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公开(公告)号：US20210406616A1
公开(公告)日：2021-12-30
申请号：US17039554
申请日：2020-09-30
Inventor： Yehui YANG , Lei WANG , Yanwu XU
Abstract: A target detection method a is provided, which relates to the fields of deep learning, computer vision, and artificial intelligence. The method comprises: classifying, by using a first classification model, a plurality of image patches comprised in an input image, to obtain one or more candidate image patches, in the plurality of image patches, that are preliminarily classified as comprising a target; extracting a corresponding salience area for each candidate image patch; constructing a corresponding target feature vector for each candidate image patch based on the corresponding salience area for each candidate image patch; and classifying, by using a second classification model, the target feature vector to determine whether each candidate image patch comprises the target.
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2.发明申请公开(公告)号：US20210406586A1
公开(公告)日：2021-12-30
申请号：US17139069
申请日：2020-12-31
Inventor： Dalu YANG , Yehui YANG , Lei WANG , Yanwu XU
Abstract: An image classification method and apparatus, and a style transfer model training method and apparatus are provided, which are relate to the field of deep learning, cloud computing and computer vision in artificial intelligence. The image classification method comprises: inputting an image of a first style into a style transfer model, to obtain an image of a second style corresponding to the image of the first style; and inputting the image of the second style into an image classification model, to obtain a classification result of the image of the second style, wherein the style transfer model is obtained through training on the basis of a sample image of the first style and a sample image of the second style; and the image classification model is obtained through training on the basis of the sample image of the second style.
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