This course introduces the fundamental concepts and applications of deep learning within the field of computer vision. You will learn how modern deep learning techniques have surpassed traditional methods that relied on hand-crafted features for tasks such as object detection, segmentation, and classification. The course aims to equip you with the skills to identify computer vision problems, implement solutions using suitable neural network architectures, and critically analyze their performance.
The course combines lectures and practical exercises to provide hands-on experience with neural networks for computer vision. You will progress from understanding specific problems to developing neural network-based solutions. Topics covered include image classification, object detection, and semantic segmentation.
Minimum 8 participants required.
International students are charged 7500 EUR per semester. The total tuition for the 2-year Master's program is 30000 EUR. Please note that fees are subject to revision for Autumn 2026.
The language of instruction for this program is English.
Prospective students must be nominated by their home institution, as DTU does not accept applications from free movers. Confirm your eligibility with your home university's international office and ensure they have an exchange agreement with DTU.
The course '02450' is recommended as a prerequisite or prior study.
The program covers fundamental concepts and applications of deep learning in computer vision, including image classification, object detection, and semantic segmentation, using neural network architectures.