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Research Focus: Week of February 19, 2024
In this issue: CaaSPER: vertical autoscaling algorithm dynamically maintains optimal CPU utilization; Improved scene landmark detection for camera localization runs faster, uses less storage; ESUS simplifies usability questionnaires for technical products and services.
Blog de recherche Microsoft
Swin Transformer supports 3-billion-parameter vision models that can train with higher-resolution images for greater task applicability
| Han Hu et Baining Guo
Early last year, our research team from the Visual Computing Group (opens in new tab) introduced Swin Transformer (opens in new tab), a Transformer-based general-purpose computer vision architecture that for the first time beat convolutional neural networks on the important…