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METHOD, APPARATUS, AND SYSTEM FOR REAL-TIME OBJECT DETECTION USING A CURSOR RECURRENT NEURAL NETWORK
METHOD, APPARATUS, AND SYSTEM FOR REAL-TIME OBJECT DETECTION USING A CURSOR RECURRENT NEURAL NETWORK
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机译:游标递归神经网络的实时对象检测方法,装置和系统
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摘要
An approach is provided for object detection. The approach involves receiving a feature map encoding high level features of object contours detected in an image divided into a plurality of grid cells, and further encoding start locations of each detected object contour. The approach also involves selecting a grid cell including a start location of an object contour. The approach further involves determining a precise location of the start location within the grid cell. The approach further involves determining a set of feature values from a set of proximate grid cells. The approach further involves processing the precise location and the set of feature values using a machine learning network to output a displacement vector to indicate a next coordinate of the object contour, and updating a cursor of the machine learning network based on the displacement vector.
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