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METHODS AND APPARATUS FOR DISCRIMINATIVE SEMANTIC TRANSFER AND PHYSICS-INSPIRED OPTIMIZATION OF FEATURES IN DEEP LEARNING
METHODS AND APPARATUS FOR DISCRIMINATIVE SEMANTIC TRANSFER AND PHYSICS-INSPIRED OPTIMIZATION OF FEATURES IN DEEP LEARNING
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机译:深度学习中区别性语义转移和物理启发式特征优化的方法和装置
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摘要
Methods and apparatus for discriminative semantic transfer and physics-inspired optimization in deep learning are disclosed. A computation training method for a convolutional neural network (CNN) includes receiving a sequence of training images in the CNN of a first stage to describe objects of a cluttered scene as a semantic segmentation mask. The semantic segmentation mask is received in a semantic segmentation network of a second stage to produce semantic features. Using weights from the first stage as feature extractors and weights from the second stage as classifiers, edges of the cluttered scene are identified using the semantic features.
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