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By using this toolbox, you can get a first impression of how CNNs can be used for computer vision applications. While you are using the toolbox, you will learn a lot about deep learning and how CNNs work.
CUDA is an open-source framework for parallel programming of NVIDIA GPUs (graphics processors). CUDA is used by many fields of research and development, including computer graphics,
computer vision, digital signal processing, scientific computing, and bioinformatics. CUDA is free for non-commercial use. For commercial use there is a license which provides access to CUDA.
Anaconda is an open-source platform for software distribution and support. It is free for individuals and educational institutions to use. Anaconda's main goal is to provide research-level software to the general public, and is designed for easy installation and management of large collections of software. Anaconda distributes software through the Python Package Index (PyPI), a repository of more than 700,000 Python packages, as well as through the Package Control system, which makes installing packages simple. Anaconda is based on and provides support for Python 2.7, 3.x, and 3.5.
You will learn CUDA programming including development of device code, GPU programming, and parallel computing. A proper understanding of this framework is crucial for an application programmer to use the NVIDIA GPU.
In this tutorial, we present how to install the MatConvNet toolbox for MATLAB 7 or later. We describe how to train and evaluate a CNN, and conclude by showing how to deploy a trained CNN to a computer running a web server.
The MatConvNet toolbox provides many pre-trained CNNs for different computer vision problems. MatConvNet is simple, efficient, and can run and learn state-of-the-art CNNs. Many pre-trained CNNs for image classification, segmentation, facerecognition, and text detection are available.
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Some applications, such as Java, require that the application directories and libraries are updated to a newer version before the user can update. However, there are some applications that are not explicitly API-specific, such as the X Window System, the X server source code, are automatically updated as required.
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