View sample code Adjusting the Brightness and Contrast of an Image Use a gamma function to apply a linear or exponential curve. View sample code Adjusting the Hue of an Image Convert an RGB image to L*a*b* color
improving deep network generalization to out-of-domain data. Our code and pre-trained models are available at https://github.com/visinf/self-adaptive. PDFPaper record Results in Papers With Code (↓ scroll down to see all results)
Metal sample code View sample code to see how Metal APIs are implemented. Featured Streaming large images with Metal sparse textures Use Metal sparse textures to render a high-resolution image without the need to allocate memory for the entire image. This sample queries a residency and access cou...
See code samples for Microsoft developer tools and technologies. Explore and discover the things you can build with products like .NET, Azure, or C++.
See code samples for Microsoft developer tools and technologies. Explore and discover the things you can build with products like .NET, Azure, or C++.
MachineLearningSample. Contribute to palanceli/MachineLearningSample development by creating an account on GitHub.
There aretwo experiments performed, the 1st experiment deals with the gender classification of ten completely different languages, every language consists of fifteen audio files and also the best accuracy achieved by the machine learning technique that's straight forward logistical (87.33%). The second...
Thus, advanced statistical tools and machine learning techniques may become essential to identifying patterns in the data and reaching reliable results. Some of the most important among these techniques, which may be applied to elemental analysis associated with the study of medical conditions, are ...
Learning any new technology is a time-consuming process where it's easy to get lost. This is why we created this series of practical, and focused modules about Node.js for beginners so you can get up to speed.You'll find all the source code used in the Learn modules and videos to ...
The purpose is mainly to simulate human learning behaviors like recognition, generation, imagination, synthesis and analysis. The second category is called "experience learning", which usually co-exists with the large sample learning manner of conventional machine learning. This category mainly focuses ...