ARMA Nets: Expanding Receptive Field for Dense Prediction

15 Feb 2020Jiahao SuShiqi WangFurong Huang

Global information is essential for dense prediction problems, whose goal is to compute a discrete or continuous label for each pixel in the images. Traditional convolutional layers in neural networks, originally designed for image classification, are restrictive in these problems since their receptive fields are limited by the filter size... (read more)

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