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1.发明申请公开(公告)号：US20200320342A1
公开(公告)日：2020-10-08
申请号：US16738804
申请日：2020-01-09
发明人： Wenqi WANG , Shiguo LIAN , Yibing NAN
摘要： A method for training an object identification neural network based on a distorted fisheye image includes: acquiring the distorted fisheye image, wherein the distorted fisheye image comprises at least one target object; dividing the distorted fisheye image into a plurality of zones according to a distortion degree; determining a zone to which each of the at least one target object belongs; categorizing the at least one target object according to the zone to which each of the at least one target object belongs; and inputting the distorted fisheye image and a category to which each of the at least one target object belongs into the object identification neural network to train the object identification neural network.
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公开(公告)号：US20200242409A1
公开(公告)日：2020-07-30
申请号：US16751254
申请日：2020-01-24
发明人： Kai WANG , Yibing NAN , Fuyuan SHI , Wenqi WANG , Yimin LIN , Shiguo LIAN
摘要： A method, a device and a terminal for generating training data is provided. The method for generating training data includes: obtaining an original image; determining a transferred image based on the image style transfer model and the original image, wherein the image style transfer model is obtained by minimizing a loss function, the loss function is determined by the original loss function the background loss function and the foreground loss function; determining the training data based on the transferred image. The difference between the generated training data and the target image is small, thereby improving the accuracy of the training model obtained by using the training data.
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