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Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads
Therefore, accurate measurements of the power draw of AI workflows on different types of compute nodes is key to algorithmic improvements and the design of future compute clusters and hardware.
Classification of diffraction patterns using a convolutional neural network in single particle imaging experiments performed at X-ray free-electron lasers
Single particle imaging (SPI) at X-ray free electron lasers (XFELs) is particularly well suited to determine the 3D structure of particles in their native environment.
How can we learn (more) from challenges? A statistical approach to driving future algorithm development
Challenges have become the state-of-the-art approach to benchmark image analysis algorithms in a comparative manner.
Representing Ambiguity in Registration Problems with Conditional Invertible Neural Networks
One example is the registration of 2D X-ray images with preoperative three-dimensional computed tomography (CT) images in intraoperative surgical guidance systems.
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