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Deep Learning in OpenCV - Wu Zhiwen, Intel

4,836 views · Published 25 October 2018 · 26:21 · Indexed 8 October 2026

Channel: The Linux Foundation · 2018 · Science & Technology

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Deep Learning in OpenCV - Wu Zhiwen, Intel

Deep Learning is the most popular and the fastest growing area in Computer Vision nowadays. OpenCV is the famous Computer Vision library. Since OpenCV 3.1 there is a deep learning module (called OpenCV DNN) introduced in the library that implements forward pass (inferencing) with deep networks, which are pre-trained using some popular deep learning frameworks, such as Caffe. tensorflow and torch. Now it support most popular networks.

This presentation will introduce OpenCV deep learning architecture, It will introduce how to setup and run a deep learning network with OpenCV DNN. It will also talk about important techniques for deep network acceleration, including convolution performance auto-tuning, layer fusion and FP16 (half-float) support. We are key contributors for this work. All these optimization are important to help user achieve best performance.

About Zhiwen Wu
Zhiwen works at Open Source Technology Center at Intel Software group. He has been working on various Linux project for over ten years, including Moblin, Meego and OpenCV. He has rich experience on Open Source project development, especially the Linux media project. He is also a contributor of OpenCV deep learning module.

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