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Classification of diffraction patterns in single particle imaging experiments performed at x-ray free-electron lasers using a convolutional neural network
Single particle imaging (SPI) is a promising method of native structure determination, which has undergone fast progress with the development of x-ray free-electron lasers. Large amounts of data are collected during SPI experiments, driving the need for automated data analysis. The necessary data analysis pipeline has a number of steps including binary object classification (single versus non-single hits). Classification and object detection are areas where deep neural networks currentlydoi:10.3204/pubdb-2022-00507 fatcat:lrcrdtifuncnvlgzgszhf5cfdi