Convolutional Neural Networks (CNN) are becoming mainstream in computer vision. In particular, CNNs are widely used for high-level vision tasks, like image classification. This article describes an example of a CNN for image super-resolution (SR), which is a low-level vision task, and its implementation using the Intel® Distribution for Caffe* framework and Intel® Distribution for Python*.
What we call deep learning is typically associated with servers, the cloud, or high-performance computing. We are witnessing a reshuffling of compute partitioning between cloud data centers and clients in favor of moving applications of deep learning models to the client.
本文（及相关教程）介绍了一个面向图像超高分辨率 (SR) 的 CNN 示例（低级视觉任务）以及如何使用英特尔® Caffe* 分发包框架和英特尔® Python* 分发包进行实施。
Release Notes of Intel® Media SDK include important information, such as system requirements, what's new, feature table and known issues since the previous release.
本文描述了如何在仅限 CPU 的环境中安装并运行 Unity Technologies ML-Agents*。本文展示了如何：在 Windows* 上训练并运行 ML-Agents，执行 TensorFlow* CMake 构建，以及从零创建一个简单的 Amazon Web Services Ubuntu* Amazon Machine Image* 环境。
At the Autodesk University event in Las Vegas, November 14-16, civil and commercial/industrial designers and manufacturers who use Autodesk software came together to see The Future of Making Things.
Windows* Machine Learning (ML) is an inference engine running on the edge on the Windows operating system (OS) and provides a very simple developer interface that will be optimized under the hood for Intel hardware.