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ARTIFICIAL NEURAL NETWORK COMBINING SENSORY SIGNAL CLASSIFICATION AND IMAGE GENERATION
ARTIFICIAL NEURAL NETWORK COMBINING SENSORY SIGNAL CLASSIFICATION AND IMAGE GENERATION
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机译:人工神经网络结合感觉信号分类和图像生成
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摘要
A method which includes: Obtaining a training set which comprises: multiple data pairs each comprising: (i) a raw sensory signal acquired by a medical imaging system, and (ii) a processed image generated by the medical imaging system from the raw sensory signal; and a classification label for each of the data pairs. Based on the training set, training an artificial neural network (ANN), wherein the training comprises minimizing a global loss which is a weighted sum of: a loss between the classification labels and classification predictions by the ANN, and a similarity loss between the processed images and images generated by an intermediate layer of the ANN. The training is such that the trained ANN is configured, for a new raw sensory signal: to predict a new classification, and to generate a new image by the intermediate layer of the ANN.
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