This course is an introduction to the process of generating a symbolic description of the environment from an image. It covers the physics of image formation, image analysis, binary image processing, and filtering, with applications in robotics and intelligent machine interaction.
This course covers the fundamentals of deep learning, including both theory and applications. Topics include neural net architectures (MLPs, CNNs, RNNs, graph nets, transformers), geometry and invariances in deep learning, backpropagation and automatic differentiation, learning theory and generalization in high dimensions, and applications to computer vision, natural language processing, and robotics.
이 과정은 간단한 교육용 비디오 게임을 설계하고 제작하며 배포하는 방법을 배우는 9일간의 실습 워크숍입니다. 참가자는 Unity 게임 엔진을 사용하여 비디오 게임을 만들고, GitHub를 통한 협업 소프트웨어 개발, Microsoft Kinect를 활용한 제스처 처리 등을 배우게 됩니다.
