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We present an atrous convolutional encoder-decoder trained to denoise 512×512 crops from electron micrographs. It consists of a modified Xception backbone, atrous convoltional spatial pyramid pooling module and a multi-stage decoder. Our neural network was trained end-to-end to remove Poisson noise applied to low-dose (≪ 300 counts ppx) micrographs created from a new dataset of 17267 2048×2048 high-dose (> 2500 counts ppx) micrographs and then fine-tuned for ordinary doses (200-2500 countsarXiv:1807.11234v2 fatcat:ijslzpsvsjbilazrzvkroj7fry