![]() A new product, GPU Coder, automatically converts deep learning models to CUDA code for NVIDIA GPUs. In addition to object detection workflows, the toolbox now also supports semantic segmentation using deep learning to classify pixel regions in images and to evaluate and visualize segmentation results. The Image Labeler app in Computer Vision System Toolbox now provides a convenient and interactive way to label ground truth data in a sequence of images. Neural Network Toolbox has added support for complex architectures, including directed acyclic graph (DAG) and long short-term memory (LSTM) networks, and provides access to popular pretrained models such as GoogLeNet. Specific deep learning features, products, and capabilities in R2017b include: ![]() ![]() The release also adds new important deep learning capabilities that simplify how engineers, researchers, and other domain experts design, train, and deploy models. MathWorks introduced Release 2017b (R2017b), which includes new features in MATLAB and Simulink, six new products, and updates and bug fixes to 86 other products. Supported Operating Systems: Windows 7even SP1 / 8.x / 10 / Server 2012 (R2) / Server 2008 R2 SP1 / Server 2016
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