Explore deep learning in OpenCV with Intel's Wu Zhiwen in this 26-minute Linux Foundation conference talk. Discover the OpenCV deep learning module (OpenCV DNN) introduced in version 3.1, which enables forward pass inferencing with pre-trained networks from popular frameworks like Caffe, TensorFlow, and Torch. Learn about OpenCV's deep learning architecture, setup processes, and network acceleration techniques, including convolution performance auto-tuning, layer fusion, and FP16 support. Gain insights into achieving optimal performance with these optimizations. Delve into topics such as OpenCV basics, Deep Neural Networks, architecture, acceleration methods, network optimization, layer fusion, OpenCL, and Vulcan backend.
Overview
Syllabus
Introduction
What is OpenCV
Deep Neural Networks
Why
Architecture
Acceleration
Network Optimization
Layer Fusion
OpenCL
Vulcan backend
Taught by
Linux Foundation
