In this engaging session, students will explore machine learning and computer vision through depth estimation and segmentation. We will cover the following key aspects:
1. Fundamentals: Students will learn the core principles behind depth estimation and segmentation, providing a solid foundation for advanced concepts.
2. Advanced Models: We'll introduce students to cutting-edge models like DinoV2 and Detectron, giving them hands-on experience in working with these powerful tools.
3. Practical Application: The session will bridge theory and practice by demonstrating how depth estimation and segmentation are used in the development of augmented reality (AR) games. This approach sparks creativity and shows the real-world impact of these technologies.
4. Industry Relevance: Students will gain insights into the practical applications of depth estimation and segmentation across various industries. This includes medical imaging for tumor detection and organ boundary identification, autonomous vehicles for road segmentation and obstacle detection, precision agriculture for crop monitoring and weed detection, and retail and fashion for virtual try-ons and product segmentation.
By the end of this session, students will have a solid understanding of depth estimation and segmentation and a broader perspective on the exciting possibilities and career opportunities in the fields of machine learning and computer vision.