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CONTEXT-BASED PRIORS FOR OBJECT DETECTION IN IMAGES
CONTEXT-BASED PRIORS FOR OBJECT DETECTION IN IMAGES
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机译:图像中对象检测的基于上下文的优先级
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摘要
Context-based priors are utilized in machine learning networks (e.g., neural networks) for detecting objects in images. The likely locations of objects are estimated based on context labels. A machine learning network identifies a context label of an entire image. Based on the context label, the network selects a set of likely regions for detecting objects of interest in the image.
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