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SUBCATEGORY-AWARE CONVOLUTIONAL NEURAL NETWORKS FOR OBJECT DETECTION
SUBCATEGORY-AWARE CONVOLUTIONAL NEURAL NETWORKS FOR OBJECT DETECTION
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机译:用于目标检测的子类-觉悟卷积神经网络
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摘要
A computer-implemented method for detecting objects by using subcategory-aware convolutional neural networks (CNNs) is presented. The method includes generating object region proposals from an image by a region proposal network (RPN) which utilizes subcategory information, and classifying and refining the object region proposals by an object detection network (ODN) that simultaneously performs object category classification, subcategory classification, and bounding box regression. The image is an image pyramid used as input to the RPN and the ODN. The RPN and the ODN each include a feature extrapolating layer to detect object categories with scale variations among the objects.
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