Objective: Ubiquitous internet access is reshaping the way we live, but it is accompanied by unprecedented challenges in preventing chronic diseases that are usually planted by long exposure to unhealthy lifestyles.
In this paper, we present an ultra lightweight system that can effectively recognize different circuit components in an image with very limited training data.
no code implementations • 28 Jul 2020 • Katy Börner, Ellen M. Quardokus, Bruce W. Herr II, Leonard E. Cross, Elizabeth G. Record, Yingnan Ju, Andreas D. Bueckle, James P. Sluka, Jonathan C. Silverstein, Kristen M. Browne, Sanjay Jain, Clive H. Wasserfall, Marda L. Jorgensen, Jeffrey M. Spraggins, Nathan H. Patterson, Mark A. Musen, Griffin M. Weber
The CCF enables contributors to HuBMAP to 'register' specimens and datasets within a common spatial reference system, and it supports a standardized way to query and 'explore' data in a spatially and semantically explicit manner.
Several ongoing international efforts are developing methods of localizing single cells within organs or mapping the entire human body at the single cell level, including the Chan Zuckerberg Initiative's Human Cell Atlas (HCA), and the Knut and Allice Wallenberg Foundation's Human Protein Atlas (HPA), and the National Institutes of Health's Human BioMolecular Atlas Program (HuBMAP).