Abstract: A computing device is configured to generate a thumbnail image. The computing device may receive a source image, downscale the source image to generate a downscaled image, process the downscaled image with a neural network to generate a non-linear thumbnail image, wherein the neural network operates according to parameters that were trained using saliency maps, and wherein the non-linear thumbnail image includes one or more non-linearly scaled salient features relative to one or more original salient features in the source image, and output the non-linear thumbnail image.

Abstract: Systems and techniques are described for image processing. For instance, an imaging system can obtain an input image with a first region and a second region, both at a first resolution. The imaging system can determine that the first region is more salient than the second region (e.g., based on a saliency map mapping saliency values to pixels of the input image). The imaging system can use a first process (e.g., using a trained network, such as of a machine learning super resolution system) to modify the first region to increase the first resolution to a second resolution. The imaging system can use a second process (e.g., based on an interpolation process) to modify the second region to increase the first resolution of the second region to the second resolution. The imaging system can generate and/or output an output image including the modified first region and the modified second region.

Abstract: Some examples may generate one or more sets of compressed images from an image collection. Images from the image collection may be clustered into one or more sets of images based on one or more features in each image. A minimum spanning tree of images may be created from each of the one or more sets of images based on the one or more features in each image. Feature-based prediction may be performed using the feature-based minimum spanning tree. One or more sets of compressed images corresponding to the one or more sets of images may be generated.

Abstract: The present invention discloses a method for realizing a dynamic adjustment of toolbar button display, which comprises: loading a toolbar through a peripheral interface and initializing the toolbar; calling a toolbar button setting interface and setting each button parameter in a toolbar button container; correspondingly adjusting display of each button in the toolbar when the toolbar is adjusted. The present invention further correspondingly discloses a system for realizing a dynamic adjustment of toolbar button display. The present invention applies a development technology of separating the button function and the button display, the specialized code and arithmetic are not needed to design for the position adjustment and arrangement of the toolbar in the process of development, so the development time of the system is greatly reduced and the development efficiency is improved.