There has been a surge of opportunities for the development of deep learning algorithms & platforms for advanced vision systems and smart robots to operate indoors (in messy living environments), underwater, and in the air (with drones). This has been boosted by the availability of high performance computing, large amounts of visual data (big data), and the recent introduction of new sensors (e.g., 3D video sensors). These systems will reduce the expensive costs associated with elder's health and home care expenses, and enhance competitiveness in agriculture & marine economies. This lecture will give a brief introduction to Computer Vision, then provides a detailed cover of Artificial neural networks, and focus on main deep learning networks, namely Convolutional Neural Networks (CNNs), Auto-encoders, Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs) and their applications in the development of vision systems.
