Abstract: A method for using a machine learning model having a base model and multiple branch models includes obtaining an image containing a face and processing the image using the base model to generate intermediate data. The method also includes processing the intermediate data using a first of the branch models to perform a first image processing task, where the first image processing task is associated with analyzing the image containing the face. The method further includes processing the intermediate data using a second of the branch models to perform a second image processing task different from the first image processing task, where the second image processing task is associated with analyzing the image containing the face. The base model and the first branch model are trained using a first dataset, and the base model and the second branch model are trained using a second dataset different from the first dataset.

Abstract: Methods and systems for visualizing information on gigapixels Whole Slide Image are described. In an example, a method for visualizing information includes providing an image viewer with a list of information to visualize, loading an image and a mask for an information source, and dynamically finding a zoom factor. If the zoom factor is not suitable for fine detailed view, then information for a coarse mask is shown. If the zoom factor is suitable for fine detailed view, then information for a fine detailed mask is chosen from a plurality of information sources.

Abstract: Memristor-based nano-crossbar computing is a revolutionary computing paradigm that does away with the traditional Von Neumann architectural separation of memory and computation units. The computation of Boolean formulas using memristor circuits has been a subject of several recent investigations. Crossbar computing, in general, has also been a topic of active interest, but sneak paths have posed a hurdle in the design of pervasive general-purpose crossbar computing paradigms. Various embodiments are disclosed which demonstrate that sneak paths in nano-crossbar computing can be exploited to design a Boolean-formula evaluation strategy. Such nano-crossbar designs are also an effective approach for synthesizing high performance customized arithmetic and logic circuits.