image super-resolution 的監督學習方法已經是一片紅海，video super-resolution 中可以利用相鄰幀之間的相互關系。 8 展望 從上面的介紹可以看出，
super resolution 超解析螢光顯微鏡 – 超高解析度顯微鏡
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Super-resolution microscopy at a glance
Defining super resolution The resolution limit of conventional light microscopy is ~250 nm in the x and y direction, and >450–700 nm in the z direction. This limit, also called the point-spread function (PSF), is the fixed size of the spread of a single point of light that is
Introduction to super-resolution microscopy
Super-resolution techniques using coherent Raman scattering and sum frequency generation were also proposed [103, 104], where molecular vibrations are utilized to visualize sample structures without labeling. These techniques would compensate fluorescence
Super Resolution API
The Super Resolution API uses machine learning to clarify, sharpen, and upscale the photo without losing its content and defining characteristics. Blurry images are unfortunately common and are a problem for professionals and hobbyists alike. Super resolution
Super-resolution microscopy demystified
· Super-resolution microscopy (SRM) bypasses the diffraction limit, a physical barrier that restricts the optical resolution to roughly 250 nm and was previously thought to be impenetrable. SRM
Super-Resolution Microscopy – an overview
Super-resolution microscopy is an ideal tool to study the spatial organization of complex MT arrays and their relationship with other cellular structures. In this chapter, we described methods for the preparation of whole-mount alfalfa root samples (originating either from seedlings or from somatic embryos) for super-resolution imaging of immunolabeled MTs using two microscopy platforms, SIM
Dynamic Super Resolution Improves Your Games With …
Dynamic Super Resolution (DSR) is a new NVIDIA technology applied through GeForce Experience, which dramatically improves the detail and quality of any game that supports resolutions over 1920×1080. Check out an enlarged comparison here. Grass is an
Image Super-resolution 的深度學習方法
例如，face image super-resolution 中可以使用其他方法進行人臉對齊，卷積神經網絡在各方面的新方法幾乎被人們在 image super-resolution 模型上試了個遍。
Super Resolution with Generative Adversarial Networks
· PDF 檔案Super-resolution via self-examplars is combination of the classical model and learning-based model [6,7]. Such method exploits the statistical prior of natural image patches that tend to recur within and across scales of the same im-age [7]. And such method
I put Adobe’s Super Resolution to the test
· I put Adobe’s Super Resolution feature through a pretty good, non-scientific test. In fact, I compared it to what I believe is currently the best enlarging software for photographs, Topaz Gigapixel Ai. In the video below you will see me compare enlargements of three
How to enable Dynamic Super Resolution in games.
· Dynamic Super Resolution (DSR) Support Reference Chart What is DSR? Multi-Frame Anti-Aliasing (MFAA) Supported Configurations and Titles How do I change my display resolution? Creating a custom resolution higher than
Super-Resolution from a Single Image
· PDF 檔案Super-Resolution from a Single Image Daniel Glasner Shai Bagon Michal Irani Dept. of Computer Science and Applied Mathematics The Weizmann Institute of Science Rehovot 76100, Israel Abstract Methods for super-resolution can be broadly classified into two
Super-resolution
Super-resolution Software We have developed a Matlab program with graphical user interface that implements several image super-resolution methods developed in this project. This application is availabe for the use of researchers and companies. The Matlab
Photoshop super resolution will quadruple your photo’s …
· Super resolution blows up a 12-megapixel smartphone photo into a much larger 48-megapixel shot. It’s coming to Lightroom soon, too. Illustration by Stephen Shankland/CNET
Photoshop’s new Super Resolution feature makes …
· Something like Super Resolution can really come in handy when you’re working with much older DSLRs. My first serious digital camera, for instance, was a Canon 10D, which promised a …
Super-resolution in Phase Space
This work considers the problem of super-resolution. The goal is to resolve a Dirac distribution from knowledge of its discrete, low-pass, Fourier measurements. Classically, such problems have been dealt with parameter estimation methods. Recently, it has been shown that convex-optimization based formulations facilitate a continuous time solution to the super-resolution problem. Here we treat